Jobs Data & Analytics

We're looking for a marketing analyst who will be the first specialist in this field on our analytics team — and who, as a result, will be able to not only carry out tasks but also directly influence how marketing analytics is structured within the company.

We value honest and transparent communication at every stage — from the first call to the job offer. Below is everything you need to know about the role to help you determine if this is the right opportunity for you. If you still have questions after reading this, feel free to reach out — we're open to dialogue.

This role is a good fit for you if:

• 3+ years of experience in marketing analytics, product-marketing analytics, or performance analytics
• Strong SQL skills — comfortable with large datasets, complex queries, and production environments
• Solid grounding in statistics: experimental design, significance, confidence intervals, and small-sample analysis
• Confident with Python for automation, data cleaning, API integrations, and recurring reporting
• Hands-on experience designing and running A/B tests
• Practical experience with marketing and tracking tools — familiarity with roughly two-thirds of the following is enough: Singular, Google Ads, Google API, Meta Ads, Google Analytics (GA4), GTM, affiliate platforms, and postbacks

• Experience building attribution logic, funnel reporting, cohort analysis, CAC/ROI/ROMI reporting, and LTV/CAC analysis

   

A plus:

• Tableau skills
• iGaming/iGambling background
• Track record leading or mentoring a team
  
  What You'll Be Doing:
• Full-cycle marketing data management: collection, transformation, cleansing, quality control, dashboard creation, and documentation
• Collecting and organizing marketing spend across all channels with precise calculations of CAC, ROI, and ROMI broken down by campaign, source, partner, keyword, landing page, source ID, and creative
• Building marketing funnels and reports based on data from landing pages and ad platforms (Facebook Ads Manager, etc.)
• Supporting A/B tests and experiments on landing pages: setting up tracking, measuring results, analyzing effectiveness, and providing recommendations on scaling, pausing, or refining
• Assisting the team in launching and evaluating marketing tests for campaigns, creatives, landing pages, sources, keywords, and traffic segments
• Developing and maintaining remarketing integrations (GA + GTM, DV360, API)
• Developing and maintaining benchmark models for the marketing team

• Working closely with the Marketing, Product, Analytics, Affiliate, and Risk teams to ensure the reliability, availability, and usefulness of data for day-to-day decision-making

   

What We Offer:

• 24 days of vacation + days off
• Remote-first — work from anywhere in the world
• Support for your learning and professional development through external courses and educational activities (conferences, webinars, etc.)
• Benefits cafeteria: a flexible budget you can spend on sports activities, English language courses, and more
• No test assignment — we assess your experience through a live conversation
• Probationary period: 3 months, with clear and straightforward expectations from day one
   

Hiring Process:

Transparent and streamlined selection process: screening call (~40 min) → technical interview (50 min) → job offer

About

We’re looking for a senior ML/AI Engineer to build Stream, a new conversational interface. As an ML/AI engineer, you will architect, build, and deploy a new interface which spans voice, audio, and agentic control. This role is perfect for someone who cares deeply about real-world ML deployment and low-latency voice interactions.

Responsibilities

• Design and improve user-facing experiences, including voice, audio, and agentic control.
• Develop, evaluate, and deploy models spanning cloud models to resource-constrained on-device settings
• Optimize inference pipelines for latency, reliability, and concurrency

• Work closely with other ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products

   

Qualifications

• 4+ years in artificial intelligence or machine learning applications
• Experience shipping ML-based products is required
• Experience in large-language models is required
• Experience in audio / voice ML is a major plus
• Comfortable writing production-grade software
• Passion for human-computer interaction

T H E  R O L E
Own the intelligence layer of Rx360 — the models that turn continuous sensor and medication data into a working understanding of each individual we serve, and turn that understanding into actions that help them stay independent. You will set the ML architecture, build the longitudinal modeling stack from raw signal through to user-facing recommendation, and define how our models and our conversational companion work together.

W H AT Y O U ' L L D O
Own the ML architecture for personalized health intelligence — per-user baselines, N-of-1 and hierarchical models, and the strategy for learning from one individual's history rather than a population mean.
Build the digital biomarker stack on raw wearable signal: gait and cadence, sit-to-stand and postural transitions, activity classification, sleep and circadian structure, and cardiovascular trend from IMU and PPG streams.
Design change detection and event-association models that link medication starts, dose adjustments, and adherence gaps to downstream behavioral shifts — with defensible handling of confounding, lag structure, and multiple comparisons.
Turn a detected change into a recommendation: what to surface, to whom (the individual, family, pharmacist, or provider), with what urgency — and when the right answer is to say nothing.
Build the data and training infrastructure that carries high-frequency time-series from device ingestion through feature generation, training, serving, and monitoring.
Own evaluation. Offline benchmarks, labeled ground truth from pilot cohorts, calibration and drift monitoring, and the false-positive budget that decides whether people trust what we tell them.
Ground our conversational companion in real signal. Our AI companion runs on a large language model inside our
HIPAA-compliant cloud environment; you will connect it to per-user model output and own the evaluation and post- training work that keeps its guidance accurate, useful, and safe.
Push inference to the edge where latency, privacy, or battery demand it, working directly with the firmware and hardware teams on what runs on the band versus in the cloud.
Direct AI coding agents to accelerate implementation while holding a rigorous quality bar — the way the rest of our engineering team works.
Partner with clinical collaborators, including our university pilot, to design studies that produce the labeled data these models actually need.
Set technical direction and raise the bar for ML across the team.

R E Q U I R E D
6+ years in machine learning, including systems you have shipped to real users and operated in production — not only research or prototypes.
Deep experience with time-series or sensor data: physiological signals, IMU / accelerometry, or comparable high- frequency multivariate streams.
Demonstrated work in individual-level modeling — per-subject baselines, hierarchical or Bayesian methods, anomaly and change-point detection, or models that adapt as data from a single person accumulates.
Strong applied statistical judgment. You can separate a real effect from a coincidence in observational data, and you know exactly where a causal claim stops being defensible.
Production-grade Python and PyTorch (or equivalent). You write software other engineers are willing to maintain.
Ownership of the full lifecycle: data pipelines, training infrastructure, deployment, monitoring, and retraining.
Experience with large-language-model evaluation and post-training — grounding and retrieval, structured output, eval harnesses, and guardrails.
Cloud-native ML at production scale (AWS preferred).
Fluent use of AI development tools (Claude Code, Cursor, Copilot, or equivalent) with the domain depth to catch where generated code fails silently.
Clear, direct communication. You can set direction across firmware, backend, mobile, design, and clinical stakeholders.

N I C E T O H AV E
Wearables, digital biomarkers, gait analysis, fall risk, or human activity recognition.
Self-supervised or foundation-model approaches for wearable time series, and comfort working under real label scarcity.
Causal inference on observational data — interrupted time series, difference-in-differences, or synthetic control.
Medication-effect modeling: polypharmacy, adherence, or PK/PD intuition.
On-device and edge ML — quantization, distillation, TinyML, inference under a power budget.
Regulated environments: HIPAA and PHI handling, model governance, or the general-wellness boundary.
Clinical research collaboration and IRB-governed data.
Voice or audio ML.

W H Y T H I S R O L E I S D I F F E R E N T
G R E E N F I E L D
You are defining the intelligence layer, not maintaining someone
else's. The architecture decisions are yours to make.
R E A L S I G N A L
Continuous, longitudinal, multi- stream data from a device we build
ourselves — with the firmware team a message away.
I T M AT T E R S
A model that catches a medication effect three days early changes
whether someone keeps living in their own home.

H O W W E W O R K
Mission comes first.
The work has real impact on people's lives. We take that
responsibility seriously.
Thoughtful technology.
Technology should simplify life, not complicate it.
Respect for independence.
The people we build for value autonomy and dignity.
Everything we create reflects that.
Curiosity.
We encourage questions, experimentation, and new ways
of thinking.

A B O U T R X 3 6 0
Rx360 is a wellness platform for older adults who want to keep living on their own terms — and for the families, pharmacists, and providers around them.
The wearable is a wrist-worn band we design in-house, carrying a PPG sensor for cardiovascular signal, a six-axis IMU for motion, gait, and posture, and on-device fall detection. The iOS and Android apps give the individual a plain- language view of their own day and their medications, and open a shared circle of care to the family members they choose to include.
Rx360 is a U.S. company headquartered in Los Angeles, California, with a distributed engineering team. Hardware, firmware, mobile, backend, and machine learning are all in-house.

About ByChat FinOps

ByChat FinOps is a production-ready B2B AI platform that helps organizations understand, analyze, and optimize cloud infrastructure costs across AWS.

Our platform combines cloud billing data with Generative AI, enabling users to ask natural language questions such as:

• Why did our cloud costs increase this month?
• Which services generate the highest expenses?
• Will we exceed our budget next quarter?
• Where can we reduce infrastructure costs?
   

Behind the scenes, intelligent LLM Agents work with cloud APIs, read-only SQL queries, billing datasets, forecasting models, anomaly detection algorithms, and FinOps analytics to deliver accurate, explainable business insights.

ByChat FinOps is an actively growing production product where AI reliability, security, scalability, and measurable business value are our highest priorities.
 

About the Role

We are looking for a Senior / Lead ML Consultant to support our engineering team on a part-time basis and provide expert guidance on the architecture, development, evaluation, and optimization of our AI/ML capabilities.

This is primarily an advisory and technical leadership role rather than a full-time hands-on engineering position.

You will work closely with our AI/ML engineers and technical team, review existing approaches and processes, identify potential risks and inefficiencies, and provide practical recommendations for improving the quality, reliability, and efficiency of our AI systems.

We expect you to act as a senior technical advisor and sparring partner for the team, helping us validate technical decisions and ensure that our ML/LLM practices meet production-grade standards.
 

What You'll Do

Your responsibilities will include:

• Review the architecture and implementation of our AI/ML and LLM-based solutions.
• Provide regular technical feedback to AI/ML engineers and help validate key engineering decisions.
• Review existing ML/LLM development processes and recommend improvements.
• Evaluate the effectiveness, reliability, and scalability of current AI workflows.
• Advise the team on the design of LLM Agents, sub-agents, tool calling, structured outputs, and agentic workflows.
• Review approaches to prompt engineering, context management, guardrails, validation, retries, and hallucination mitigation.
• Assess and improve LLM evaluation methodologies, automated testing, golden datasets, and quality metrics.
• Advise on AI observability, tracing, monitoring, and production quality control.
• Review Text-to-SQL approaches and help ensure safe and reliable interaction with financial datasets.
• Provide guidance on anomaly detection, forecasting, and other ML components used within the platform.
• Identify performance bottlenecks and opportunities to optimize LLM latency, token usage, infrastructure usage, and operational cost.
• Help the team evaluate new AI/ML technologies, frameworks, models, and architectural approaches before introducing them into production.
• Participate in technical discussions and architecture reviews for complex AI-related features.
• Mentor engineers and help strengthen the team's ML/LLM engineering practices.
• Help establish practical engineering standards and best practices for building production-grade AI systems.
   

What We Expect

Must Have

• Strong senior-level commercial experience in Machine Learning / AI Engineering, ideally including technical leadership or consulting responsibilities.
• Proven experience designing and reviewing production AI/ML systems.
• Strong practical experience with modern LLM applications and Agentic AI systems.
• Deep understanding of:
  • LLM Agents and agentic workflows
  • Prompt Engineering
  • Function / Tool Calling
  • Structured Outputs
  • Context management
  • Hallucination mitigation
  • Guardrails and validation
  • Retry and fallback strategies
• Strong understanding of ML/LLM evaluation methodologies and how to measure AI system quality in production.
• Experience with AI observability, tracing, testing, and monitoring.
• Strong Python and SQL knowledge with the ability to review implementation and architecture decisions.
• Understanding of statistics, anomaly detection, forecasting, and data-driven system evaluation.
• Experience identifying technical risks, architectural weaknesses, and performance bottlenecks.
• Ability to translate complex technical findings into clear, practical recommendations for an engineering team.
• Strong communication and mentoring skills.
• English sufficient for technical discussions, documentation, and regular communication with the team.
   

Nice to Have

• Previous experience as a Lead ML Engineer, ML Architect, AI Architect, Staff/Principal ML Engineer, or ML Consultant.
• Experience with LangChain, LangGraph, or other Agent frameworks.
• Experience with AWS Bedrock, Claude, or other managed LLM platforms.
• Experience with FinOps, cloud billing, or cloud cost optimization.
• Knowledge of:
  • AWS CUR
  • AWS Cost Explorer
• Experience with Langfuse, LangSmith, RAGAS, or similar AI observability and evaluation platforms.
• Experience designing evaluation pipelines and golden datasets for LLM applications.
• Experience with forecasting and time-series analysis.
• Experience processing large financial or billing datasets.
• Understanding of multi-tenant architectures and secure AI tool execution.
• Experience optimizing LLM latency, token usage, and operational costs.
   

Technology Stack

• Python 3.12
• FastAPI
• LangChain
• LangGraph
• AWS Bedrock
• PostgreSQL
• SQL
• Langfuse
• RAGAS
• Docker
• Next.js / TypeScript
   

Engagement Format

• Part-time consulting engagement
• Flexible involvement based on project and team needs
• Regular technical reviews and consultations with the AI/ML team
• Architecture and solution reviews for key AI/ML initiatives
• Focus on technical guidance, quality assurance, process improvement, and mentoring rather than day-to-day feature implementation
   

Why Join Us?

• Influence the technical direction of a real production AI product without committing to a full-time role.
• Work on challenging problems at the intersection of Generative AI, Agentic AI, Cloud, and FinOps.
• Help shape the architecture and engineering practices behind production-grade AI systems.
• Work with a team that values measurable AI quality, reliability, security, and business impact.
• Apply your senior-level expertise where it has the highest impact: technical decisions, architecture, evaluation, optimization, and team development.
• Stay close to modern AI technologies while working in a flexible consulting format.

About the Role

Deep Knowledge Group is seeking a Business Intelligence Analyst to convert operational, commercial and project data into clear management intelligence.

This role is distinct from Market Intelligence.

The Market Intelligence Analyst primarily examines external markets and competitors. The Business Intelligence Analyst primarily asks:

What is happening inside our projects, products and commercial pipelines, why is it happening, and what should management do next?
 

Key Responsibilities

• Build structured reporting around business and project KPIs.
• Analyze revenue, commercial pipeline, conversion, project progress, product usage, costs and operational performance.
• Consolidate information from CRM systems, project trackers, spreadsheets, dashboards and other internal sources.
• Develop management dashboards and recurring executive reporting.
• Identify performance trends, bottlenecks, anomalies and underperforming areas.
• Build simple business cases, financial scenarios and commercial models.
• Analyze funnel performance across marketing, Business Development and partnerships.
• Track product or project performance against plans, milestones and expected outcomes.
• Support management with scenario analysis and decision-ready comparisons.
• Develop forecasts where the underlying data supports them.
• Improve definitions and consistency of business KPIs across teams.
• Coordinate with Data Science where more sophisticated analytical models are required.
• Use external research where necessary to benchmark internal performance.
• Automate recurring data collection and reporting where practical.
• Use AI tools for synthesis, analysis and workflow acceleration while maintaining control over underlying data and calculations.
• Present conclusions succinctly to senior management.
   

Requirements

• 2+ years in Business Intelligence, analytics, strategy, finance, operations analytics or a comparable role.
• Advanced Excel and/or Google Sheets capability.
• Experience building dashboards and management reporting.
• Ability to work with data from multiple imperfect sources.
• Strong analytical reasoning and ability to identify the business implication behind a number.
• Understanding of business KPIs, commercial funnels and operating metrics.
• Strong written and spoken English.
• High attention to detail.
• Ability to work independently and challenge inconsistent data.
   

Strong Advantages

• SQL experience.
• Power BI, Tableau, Looker or similar BI experience.
• Python or other analytical-programming experience.
• Experience with CRM and sales-pipeline data.
• Experience in technology, investment, SaaS, professional services or multi-project environments.
• Financial-modelling or econometrics background.
   

What Success Looks Like

Management should not need to spend hours reconstructing what is happening from separate spreadsheets and messages.

The Business Intelligence Analyst should make the current state, major changes, risks, bottlenecks and decision points visible quickly and reliably.

About the Role

Deep Knowledge Group is seeking Market Intelligence Analysts to research complex technology and innovation markets and translate fragmented external information into clear, decision-ready intelligence.

DKG is a data-driven consortium active across DeepTech and Frontier Technologies, including AI, Longevity, BioTech, FinTech, GovTech, SpaceTech and other advanced industries. Its analytical work supports market intelligence, investment analysis, product development, business development and strategic decision-making.

This role focuses specifically on what is happening outside the organization: markets, competitors, companies, investors, customers, technologies, geographies and emerging opportunities.
 

Key Responsibilities

• Define and structure markets, sectors and analytical categories.
• Conduct market sizing, segmentation and growth analysis.
• Identify major companies, investors, products, technologies and ecosystem participants.
• Conduct competitor benchmarking and comparative analysis.
• Analyze business models, pricing, positioning and market-entry strategies.
• Track market developments, funding, M&A, partnerships, product launches and regulatory or technological changes.
• Build and maintain structured company, investor and ecosystem databases.
• Use OSINT methods to identify and validate relevant information from public sources.
• Analyze specific target companies or accounts for strategic and commercial purposes.
• Identify market gaps, underserved segments and emerging commercial opportunities.
• Produce concise market-intelligence reports, executive summaries, dashboards and presentations.
• Support Product Development with evidence on customer needs and competitive positioning.
• Support Business Development and MarTech with target-segment and account intelligence.
• Maintain transparent source tracking for important facts, figures and assumptions.
• Use AI tools to accelerate research, classification, comparison and synthesis while independently checking important conclusions.
   

Requirements

• 2+ years of experience in market intelligence, competitive intelligence, consulting, research, investment analysis or a comparable analytical function.
• Strong desk-research and OSINT capability.
• Strong analytical and critical-thinking skills.
• Experience working with structured datasets and spreadsheets.
• Ability to distinguish meaningful market signals from promotional noise.
• Ability to present complex information clearly and concisely.
• Strong English writing and presentation skills.
• High level of accuracy and source discipline.
• Ability to rapidly learn unfamiliar technology sectors.
   

Strong Advantages

• Experience with technology, investment, AI, DeepTech, FinTech, HealthTech or comparable innovation markets.
• Experience producing industry databases or ecosystem maps.
• Familiarity with SQL, Python, BI tools or advanced spreadsheet analysis.
• Experience with investor/company databases.
• Experience building market sizing or forecasting models.
   

What Success Looks Like

A strong Market Intelligence Analyst should be able to enter an unfamiliar market and rapidly create a reliable picture of: what the market is, who matters, where value is concentrated, what is changing, where DKG or its counterparties could have an advantage, and what evidence supports that conclusion.

About the Role

Deep Knowledge Group (https://www.dkv.global/) is seeking a senior specialist in graph intelligence, knowledge graphs and advanced network visualization to help turn large entity datasets into usable relationship intelligence.

Across DKG's analytical platforms, the important question is often not merely “what entities exist?” but:

How are they connected? Which relationships matter? Where are the clusters, central actors, hidden dependencies, emerging ecosystems and strategic gaps?

DKG maintains and develops complex datasets covering companies, investors, technologies, industries, experts, institutions, partnerships, geographical ecosystems and other interconnected entities. The objective of this role is to transform these relationships into scalable analytical systems and interactive intelligence products.
 

Key Responsibilities

• Design graph data models for complex multi-entity analytical datasets.
• Develop knowledge graphs and network-intelligence systems connecting companies, investors, technologies, people, institutions, projects, geographies and other entity types.
• Build pipelines for transforming structured and semi-structured datasets into graph-ready data.
• Work on entity normalization, relationship definitions and graph-schema design.
• Apply network-analysis methods including centrality, clustering, community detection, connectivity analysis and relationship mapping.
• Identify strategically relevant patterns and relationships that conventional tables and dashboards may not reveal.
• Develop interactive graph interfaces that allow users to explore networks without producing unreadable “hairball” visualizations.
• Create layered views, filters, drilldowns and contextual information that make large graphs operationally useful.
• Integrate graph analytics into DKG dashboards, ecosystem platforms and intelligence products.
• Work with data engineers and analysts to ensure graph outputs are analytically valid.
• Build reusable graph components and analytical frameworks for application across different DKG industries.
• Explore graph machine learning or predictive relationship analytics where these provide genuine practical value.
• Document graph schemas, relationships and analytical methodology.
   

Required Skills

• Strong practical experience with graph analytics, network science, knowledge graphs or closely related work.
• Strong Python skills.
• Experience with NetworkX, igraph or comparable graph-analysis libraries.
• Experience with graph databases such as Neo4j, Memgraph, ArangoDB or equivalent.
• Strong understanding of graph schemas, nodes, edges, properties and relationship modelling.
• Experience with advanced graph visualization tools or frameworks such as D3.js, Sigma.js, Graphistry, Gephi or similar.
• Experience cleaning and structuring complex real-world datasets.
• Ability to convert analytical requirements into appropriate graph structures and algorithms.
• Strong understanding of visual usability for large and complex networks.
• Ability to explain graph-derived findings in practical strategic terms.
• Strong English communication skills.
   

Strong Advantages

• Experience with graph machine learning, embeddings or link-prediction techniques.
• Experience with PyTorch Geometric, DGL or comparable graph-ML frameworks.
• Experience building market-intelligence, investment-intelligence, OSINT or ecosystem-mapping products.
• Experience with entity resolution and ontology/taxonomy design.
• Experience integrating graphs into production web applications.
• Familiarity with AI-assisted coding and analytical workflows.
• Exposure to investment analytics, AI, DeepTech, Life Sciences or other complex knowledge domains.
   

What Makes This Role Different

We are not looking for somebody whose main output is visually impressive network diagrams.

The purpose of graph intelligence at DKG is to expose relationships that improve actual analysis and decision-making—for example:

• identifying important companies or investors inside an ecosystem;
• mapping technology-to-company-to-investor relationships;
• identifying clusters and emerging technological concentrations;
• visualizing stakeholder and partnership ecosystems;
• tracing relationships between projects, organizations, markets and strategic opportunities.

The successful candidate must therefore combine graph engineering, analytical reasoning and visual-product design.
 

What Success Looks Like

A successful Graph Intelligence Specialist will create graph systems that become reusable infrastructure across DKG's analytical products: technically robust, analytically meaningful and sufficiently intuitive that users can extract useful insights without needing to understand graph theory.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.
   

We are currently looking for a Junior Data Analyst to join our growing Tax Data CoE team and support international tax and compliance projects through data analysis, validation, reporting, and process improvement initiatives.

In this role, you will work with large datasets from various client systems, helping teams transform raw data into meaningful insights. You will collaborate closely with data engineers, tax specialists, and engagement teams to ensure data quality, support reporting activities, and contribute to the development of scalable data-driven solutions. The role offers exposure to modern PwC technologies, including Workbench, Databricks, Power BI, and Data Controls Engine (DCE).

Key responsibilities:

• Data Extraction & Processing: Extract, prepare, and analyze data from SAP, Oracle, and other enterprise systems.
• Data Quality & Validation: Perform data validation, reconciliation, and quality checks to ensure accurate and reliable datasets.
• Reporting & Analytics: Create reports, dashboards, and actionable business insights using Excel, Power BI, and SQL.
• Data Automation: Support automation of data collection, transformation, and reporting processes.
• Collaboration: Work closely with engagement teams, tax specialists, and data professionals to deliver data-driven solutions.

Who We're Looking For:

• Junior or Middle-level Data Analyst with up to 2 years of relevant experience.
• Good knowledge of SQL and at least one of the following technologies: Alteryx, Python, or Databricks.
• Experience with data analysis, validation, and reporting activities.
• Familiarity with SAP and/or Oracle databases would be a strong advantage.
• Strong analytical and problem-solving skills.
• Excellent written and spoken English (B2+).

Nice to Have:

• Experience with Power BI, Databricks, or cloud-based analytics platforms.
• Exposure to data warehousing or data platforms.
• Knowledge of financial, tax, or compliance-related data.
• Experience working with large datasets and data transformation activities
  
  Policy statements:
  https://www.pwc.com/ua/uk/about/privacy.html

About Deep Knowledge Group

Deep Knowledge Group (https://www.dkv.global/) builds large-scale analytical databases, investment-intelligence systems, industry ecosystem platforms, competitiveness indices and interactive dashboards across frontier industries including AI, Longevity, HealthTech, DeepTech and QuantumTech.

Our products often involve complex, multidimensional datasets that need to become clear decision-making tools, not simply charts.
 

About the Role

We are seeking a Data Visualization Specialist who can transform complex analytical outputs into intuitive, high-quality interactive visual products.

This role sits between data analysis, frontend visualization and information design. The successful candidate should be capable of understanding what a dataset actually means, selecting the most appropriate visual structure, and implementing it in a form that executives, investors, analysts and other users can understand quickly.

This is not primarily a graphic-design role. Candidates must be comfortable working directly with structured data, APIs and analytical logic.

Key Responsibilities

• Develop interactive dashboards, charts, maps, analytical interfaces and other data-rich visual products.
• Transform complex datasets into clear narratives, comparisons, rankings, trends and decision-support views.
• Select visualization types based on the analytical question rather than defaulting to repetitive chart formats.
• Work directly with analysts and data scientists to understand source data, calculations, assumptions and intended user decisions.
• Develop reusable visualization components that can be applied across multiple DKG platforms.
• Build and maintain interactive visualizations using Python and/or modern JavaScript visualization libraries.
• Integrate data from APIs, databases, Google Sheets and other structured sources.
• Optimize visualization performance for large datasets.
• Improve existing dashboards for readability, responsiveness, visual hierarchy and user experience.
• Ensure labels, units, scales, filters and analytical distinctions are accurate and unambiguous.
• Test visualizations across devices and browsers.
• Use AI-assisted development tools effectively while independently reviewing generated code and analytical outputs.
• Contribute to internal standards for advanced data visualization and analytical storytelling.
   

Required Skills

• Strong portfolio demonstrating sophisticated data visualization work.
• Strong practical experience with Python-based data processing and visualization.
• Experience with libraries/frameworks such as Plotly, D3.js, ECharts, Vega/Vega-Lite or comparable tools.
• Good understanding of Pandas and structured-data manipulation.
• Experience building interactive dashboards or web-based analytical applications.
• Ability to work with APIs and external data sources.
• Strong understanding of visual hierarchy, information density and analytical storytelling.
• Ability to explain complex data clearly to non-technical audiences.
• Strong English communication skills.
• Ability to independently learn unfamiliar industries, taxonomies and datasets.
   

Strong Advantages

• Experience with Flask, FastAPI, React or comparable web application frameworks.
• Experience creating geographical, temporal, hierarchical or multidimensional visualizations.
• Experience with financial, investment, market-intelligence or scientific datasets.
• Knowledge of statistics and analytical methodology.
• Experience designing executive-grade dashboards rather than purely operational BI reports.
• Familiarity with AI-assisted coding and visualization workflows.
   

What We Will Evaluate

Candidates should be prepared to demonstrate actual previous work.

We will place particular weight on whether you can take a difficult dataset and make its main analytical distinctions immediately legible—without oversimplifying the underlying information.

The strongest candidates will combine analytical discipline with strong visual judgment and technical implementation ability.

RedCore is an international business group that creates technological solutions for digital markets. Our products and services cover fintech, marketing, e-commerce, customer service, communications, and regulatory technologies.

We are looking for a Senior Data Scientist to join our team!  

Requirements: 
- Proven experience in analysis large amount of data;
- Experience in solving customer behaviour prediction tasks;
- Knowledge of ML algorithms for regression, classification, clustering, ability to apply them to business problems;
- Solid experience in SQL;
- Extensive experience with Python for data processing, modeling, and visualization.;
- Deep understanding of statistics, probability theory;
- Passion to drive projects from R&D to business value. 

Will be a plus: 
- Familiarity with AWS infrastructure and toolchain (SageMaker, CloudFormation, CloudWatch, etc.);
- Familiarity with BI tools (Metabase, Tableau);
- Experience with tools for managing ML workflows;
- Knowledge and experience with algorithms and data structures;
- Knowledge of OOP;
- Understanding of containerization technologies (Docker)
participation in Kaggle competitions. 

Responsibilities: 
- Develop and deploy predictive models for Customer Lifetime Value (LTV) to optimize marketing spend and improve retention strategies
- Developing and testing machine learning models for customer behaviour prediction, deploying to production;
- Working with tabular data - collecting, cleaning, and exploring datasets, building ML pipelines;
- Applying statistical methods to analyze and interpret data, finding patterns, insights to improve the quality of models;
- Maintaining existing models;
- Communicating and presenting results. 

Our benefits to you:

☘️An exciting and challenging job in a fast-growing business group, the opportunity to be part of a multicultural team of top professionals in Development, Architecture, Management, Operations, Marketing, Legal, Finance, and more

🤝🏻Great working atmosphere with passionate experts and leaders, sharing a friendly culture and a success-driven mindset is guaranteed

🧑🏻‍💻Modern corporate equipment based on macOS or Windows and additional equipment are provided

🏖Paid vacations, sick leave, personal events days, days off

💵Referral program — enjoy cooperation with your colleagues and get the bonus

📚Educational programs: regular internal training sessions, compensation for external education, attendance of specialized global conferences

🎯Rewards program for mentoring and coaching colleagues

✈️In-house Travel Service

🦄Multiple internal activities: online platform for employees with quests, gamification, presents and news, clubs for movie / book / pets lovers and more

🎳Other benefits could be added based on your location 

About Farsight Vision:

Farsight Vision develops AI-powered geospatial intelligence solutions for defence and security operations. The platform transforms raw aerial and sensor data into real-time 3D environments, actionable analytics, and AI-assisted operational scenarios, enabling enhanced situational awareness, mission planning, and faster decision-making for both human operators and autonomous systems. We operate at the intersection of geospatial data, computer vision, and defense operations – and if that interests you, read on.

We are looking for a Robotics Engineer to own motion control for our unmanned ground vehicle (UGV) end-to-end – from control theory on paper to a robot that actually moves the way you designed it to. This is not a role for someone who wants control loops handed to them pre-tuned: you will design, implement, and validate them on hardware yourself

Responsibilities:   

- Implement navigation and control algorithms for different types of UGVs: differential drive, tracked wheels, Ackermann steering, etc

- Design and implement control algorithms (PID and beyond) that translate navigation commands into reliable robot motion

- Own the control stack end-to-end – from algorithm design through tuning and validation on the physical unit

- Simulate physical driving for different types of wheels and terrains before deploying to hardware

- Work closely with the Robotics team on actuator and sensor integration, since control quality is only as good as what it's built on

- Debug control issues that only show up in the field, not in simulation – this role is hands-on with the physical robot in Lviv

- Collaborate with the Perception Engineer so control decisions correctly account for obstacle and environment data

- Propose architecture and design decisions rather than waiting to be handed a fully-scoped ticket: this is a small team building a new capability almost no one in the Ukrainian market has shipped yet

 
Requirements:   

- Strong mathematical foundation: linear algebra, calculus, and the algorithmic thinking control systems are built on

- Practical experience with control theory – PID control at minimum, ideally more advanced control approaches

- Background in robotics, guidance, or navigation systems (e.g., autonomous vehicle guidance, drone terminal guidance, or similar)

- Experience with physics simulators (e.g. Gazebo, NVIDIA Isaac, MATLAB, Simulink), with the ability to simulate dynamic models and verify controller performance before deployment

- Experience working with sensors such as IMU, LiDAR, etc.

- Knowledge of state estimation and filtering (e.g. Kalman filter, extended Kalman filter, complementary filter)

- Solid programming skills in C++ (and Python for prototyping)

- Good OOP skills — ability to write and design clean code that's flexible to extend and maintain

- Comfortable working close to hardware, not purely in a software abstraction layer

- Upper-Intermediate+ English

Nice to have:

- Experience with ROS/ROS2

- Path planning algorithms (A*, D*, RRT, etc.)

- Prior work on UAV or UGV guidance/navigation systems

- Defense-tech or military-tech industry exposure

- Embedded systems or hardware-adjacent experience

 
Security Eligibility

Our platform is actively used by the Armed Forces in live operations. As an Estonian-Ukrainian defence technology company handling sensitive operational data, we have a responsibility – legal, ethical, and practical – to ensure the integrity of everyone on our team.

All candidates must be able to confirm the following:

Neither you nor your close relatives (parents, spouse, siblings, children) reside in Russia, Belarus, or temporarily occupied Ukrainian territories

You have no regular personal, financial, business, or professional contact with individuals in those territories

You consent to a deeper security verification if the process advances to later stages

If any of the above criteria are not met, please do not proceed with your application.

 
Why Farsight Vision   

We are a startup operating under real-world conditions – our product is in active deployment, and the pace reflects that. We are not a company where you get to run the same experiment three times until it's elegant – we need someone who wants to see their control loop working on a real robot within weeks, not quarters, and who is motivated by the fact that what you build here gets used, not shelved.

Flexible working hours. Paid vacation and sick leave. Direct access to founders and leadership.

About Blue Carrot

Blue Carrot is a full-service agency specializing in educational content creation and commercial video production. Since 2014, we have worked with 300+ clients worldwide, including the United Nations, DNB, Takeda, the University of Southern California, and Charité Medical University.

The role

We are looking for an Argument & Logical Coherence Analyst to help us objectively evaluate the logic and structure of educational content.

Sometimes clients question whether a course is logical, well-structured, or easy to follow. We need someone who can go beyond subjective editorial feedback and reconstruct and visualize how the text actually works: what each idea is doing, how ideas depend on one another, what supports each claim, and where logical gaps or unnecessary content exist.

Responsibilities

• Reconstruct the logical structure of a text: claims, premises, evidence, explanations, assumptions, objections, and conclusions
• Analyze dependencies between ideas and whether the reader receives the necessary information at the right time
• Identify logical gaps, unsupported claims, repetition, disconnected or unnecessary content
• Create argument/dependency maps or diagrams showing the structure at both high and detailed levels
• Provide evidence-based conclusions that can be used to explain to a client why the content is logically sound or exactly where the problems are

Requirements

• Excellent written and spoken English
• Strong analytical and critical-thinking skills
• Ability to analyze complex texts and relationships between ideas
• Ability to visually represent logical structure, not only describe it in writing
• Ability to support conclusions with specific evidence from the text

Nice to have

• Background in argumentation, informal logic, critical thinking, discourse/coherence analysis, or developmental/substantive editing
• Experience with argument mapping, claim–evidence mapping, or dependency mapping
• Experience with tools such as Argdown or similar
• Understanding of instructional design or experience with educational content

Important:: This is manual analytical work, not an NLP, computational linguistics, or automated argument-mining role. We are looking for someone who can make the architecture of a text visible and objectively evaluate whether it works.

Are you passionate about building scalable Big Data solutions and optimizing high-load platforms? We are looking for a Senior Big Data Engineer to join a long-term project in the cybersecurity and AdTech domain focused on real-time risk assessment for digital advertising ecosystems.

We at Sigma Software offer the opportunity to work on impactful products, collaborate with experienced engineering teams, and contribute to solutions operating on large-scale datasets in a fast-paced environment. You will have the freedom to influence technical decisions and drive meaningful improvements across the platform.

CUSTOMER

Our Customer operates in the cybersecurity domain and develops solutions aimed at protecting organizations and digital ecosystems from online risks and vulnerabilities. The company focuses on building advanced technologies that improve security, reliability, and operational resilience across various industries. 

PROJECT

The project is a real-time risk assessment platform for digital advertising ecosystems. The solution helps customers identify potentially low-quality or fraudulent traffic and automatically make decisions before allocating advertising budgets. The platform processes large-scale data streams and requires continuous improvements in performance, scalability, and cost efficiency.

At the initial stage, the role will focus on Snowflake optimization and identifying inefficiencies in data pipelines and SQL queries. In the long term, the engineer will contribute to backend development, platform architecture improvements, and implementation of scalable Java-based services.

RESPONSIBILITIES:

• Optimize Snowflake usage and improve infrastructure cost efficiency
• Identify inefficiencies in data pipelines and SQL queries
• Implement performance and cost optimization improvements
• Enhance and maintain Java-based services
• Implement and support new platform features
• Improve existing engineering processes and platform components
• Develop scalable and reliable solutions for high-load environments
• Contribute to architecture improvements and implementation of new components
• Collaborate with distributed engineering teams to deliver stable platform functionality

REQUIREMENTS: 

• At least 5 years of commercial experience in Big Data engineering
• Strong hands-on experience with Snowflake
• Strong expertise in Python
• Strong expertise in Java
• Advanced SQL knowledge and experience optimizing complex queries
• Solid Computer Science fundamentals
• Upper-Intermediate or higher English level

WILL BE A PLUS

• Experience with AWS cloud services
• Experience working with Amazon S3
• Experience in AdTech, cybersecurity, fraud detection, or risk assessment domains

PERSONAL PROFILE

• Proactive and ownership-driven mindset
• Strong analytical and troubleshooting skills
• Ability to work effectively in fast-paced environments
• Team-oriented communication style
• Focus on scalable and maintainable engineering solutions

Are you passionate about cybersecurity research and uncovering sophisticated attack patterns? We are looking for a Threat Research Analyst to join a remote team working on advanced application protection solutions for a global Customer in the cybersecurity domain.

In this role, you will investigate suspicious activity, analyze attack vectors, and help improve detection and blocking mechanisms for modern web applications. You will work with monitoring systems, behavioral analytics, and threat intelligence data to proactively identify emerging threats and strengthen platform security.

We at Sigma Software offer the opportunity to work on impactful security products, collaborate with experienced professionals, and grow your expertise in modern cybersecurity technologies while working remotely within European time zones.

CUSTOMER
Our Customer is a global cybersecurity company delivering comprehensive security solutions for businesses, organizations, and digital ecosystems. Operating across multiple industries, the company focuses on preventing cyber threats, identifying vulnerabilities, and protecting web applications from sophisticated automated attacks. 

PROJECT
The project is focused on building a security platform that safeguards applications from automated attacks and malicious traffic. The Threat Research team investigates emerging attack techniques, analyzes suspicious behavioral patterns, and develops detection and blocking mechanisms to improve overall protection capabilities.

As part of the team, you will work with logs, dashboards, threat intelligence data, and monitoring systems to uncover new attack vectors and enhance application security in real-world environments.

RESPONSIBILITIES:

• Monitor existing threats and investigate suspicious activities using logs, dashboards, and detection systems
• Analyze attack patterns and build detailed threat scenarios based on collected data
• Research and respond to reported threats, Customer escalations, and security incidents
• Improve detection and blocking mechanisms for automated attacks and malicious behaviors
• Analyze intelligence from competitors, public sources, and industry trends to identify emerging threats
• Work with monitoring and analytics tools such as Kibana and Elasticsearch
• Collaborate with engineering and security teams to improve product protection capabilities
• Document findings, attack methodologies, and investigation results

REQUIREMENTS:

• At least 3 years of commercial experience in cybersecurity, threat research, or related areas
• Hands-on experience in cybersecurity, threat detection, security research, threat hunting, anti-bot solutions, fraud and abuse detection, application security, or a closely related security domain.
• Strong understanding of attacker tactics, techniques, and behaviors, including methods used to evade, bypass, or modify attacks to avoid detection.
• Experience investigating suspicious or malicious activities, with a solid understanding of detection, alerting, and blocking mechanisms.
• Strong understanding of web technologies and architecture, including:
  • Client-server architecture
  • HTTP/HTTPS protocols
  • REST APIs and web services
  • Request/response lifecycle
  • Headers, cookies, sessions, and authentication mechanisms
• Understanding of browser technologies and experience investigating:
  • DOM structure and manipulation
  • Browser events
  • XHR and Fetch requests
  • WebSockets
  • Browser APIs
  • Browser security policies and controls
• Ability to read and analyze JavaScript code, identify application behavior, detect suspicious or incorrect logic, and understand potential remediation approaches. Deep JavaScript development expertise is not required.
• Working knowledge of HTML and CSS sufficient to investigate and understand web application behavior.
• Strong practical experience with SQL for data analysis, investigations, and working with large datasets.
• Hands-on experience using Kibana for log analysis, monitoring, and investigations.
• Solid understanding of networking fundamentals, including:
  • TCP/IP
  • DNS
  • VPN technologies
  • Proxies
  • Basic network troubleshooting
• Ability to independently investigate complex technical issues and correlate multiple data points to build a complete attack or incident scenario.
• Experience using AI-powered tools and chatbots for research and technical investigations, including the ability to write effective prompts and interpret results.
• Upper-Intermediate (B2) or higher level of English.

WILL BE A PLUS

• Understanding of Elasticsearch and its ecosystem.
• Python scripting and automation skills.
• Experience developing, analyzing, or investigating crawlers, scrapers, or browser automation tools.
• Experience with deobfuscation and/or reverse engineering techniques.
• Experience investigating bot traffic, automated attacks, scraping activity, credential stuffing, account takeover attempts, abuse, fraud, or similar threats.
• Experience with monitoring, analytics, and observability platforms such as Datadog, Imply, Splunk, Microsoft Sentinel, OpenSearch, or similar tools.

PERSONAL PROFILE

• Strong analytical and investigative mindset
• Attention to detail and ability to identify unusual behavioral patterns
• Curiosity about cybersecurity threats and attacker techniques
• Ability to work independently in a fast-paced environment
• Strong communication and collaboration skills
• Proactive approach to problem-solving and continuous learning

Stay Group is an innovative Marketing company with a mission to help businesses acquire their target customers and create top-tier solutions in the iGaming and entertainment industry. Currently, we are looking for our perfect DevOps Engineer to join our team and help us build scalable, reliable, and secure infrastructure.

Requirements:

• 3+ years of commercial experience as a DevOps Engineer.
• Strong hands-on experience with Kubernetes (GKE, EKS, and self-hosted clusters).
• Experience deploying and maintaining cloud infrastructure on AWS and/or Google Cloud Platform.
• Experience with CI/CD pipelines using GitLab CI/CD.
• Strong knowledge of Docker and containerized application deployment.
• Experience configuring and managing Cloudflare services, including WAF, SSL/TLS, DNS, and API automation.
• Experience with monitoring, logging, and observability tools:
  • Prometheus,
  • Grafana,
  • ELK Stack.
• Experience with database administration:
  • MySQL,
  • PostgreSQL,
  • MongoDB.
• Understanding of cloud cost optimization (FinOps).
• Experience with Infrastructure as Code and automation.
• Strong troubleshooting, analytical thinking, and ownership mindset.
• English level sufficient for reading technical documentation and communicating with international teams.

Will be a plus:

• Experience with Datadog (APM, RUM, Logs).
• Experience configuring Global Load Balancers in Google Cloud.
• Experience building scalable, high-load infrastructure.

Key Responsibilities:

• Design, build, and maintain highly available cloud infrastructure.
• Configure and manage Cloudflare services, including WAF, SSL/TLS, DNS, and API automation.
• Deploy, maintain, and optimize Kubernetes clusters across GKE, EKS, and self-hosted environments.
• Build and improve CI/CD pipelines using GitLab CI/CD.
• Automate Docker image builds and deployment processes.
• Implement and maintain monitoring, logging, alerting, and observability solutions using Prometheus, Grafana, and ELK.
• Optimize cloud infrastructure performance, scalability, and cost efficiency.
• Configure auto-scaling and load balancing for cloud environments.
• Administer and support production databases.
• Collaborate closely with Development, QA, Product, and Security teams to improve infrastructure reliability and delivery processes.

Benefits

Freedom to choose where to work: work from anywhere in the world with the freedom of remote options.

Flexibility: enjoy flexible working hours that let you balance your personal and professional life while staying focused on delivering great results.

Corporate English speaking club: improve your English proficiency with regular practice and expert guidance.

A Culture That Cares: thrive in a friendly environment where a strong corporate culture builds connections, drives innovation, and makes you feel truly valued.

Accelerate Your Growth: seize career advancement opportunities in a rapidly expanding marketing company. As the company scales, so will your professional journey.