Jobs Data & Analytics

Level: Senior Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to design, build, and own significant components of the core query engine of a large-scale distributed data platform. You will lead work across query planning, optimization, and execution — driving architectural decisions, mentoring middle engineers, and pushing the platform's performance and scalability boundaries across all major clouds.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Architect, design, and implement significant components of the query engine — planner, optimizer, execution operators, memory management, and data access layers.
• Write and review high-quality, performance-critical code in Java and/or C++.
• Own end-to-end delivery of features from technical design through production rollout.
• Drive performance optimization work — profiling, benchmarking, and eliminating bottlenecks in latency- and throughput-sensitive paths.
• Integrate deeply with columnar formats, open table formats, and connectivity drivers.
• Mentor middle engineers, lead code reviews, and set technical standards for the team.
• Contribute to CI/CD architecture and quality processes across Jenkins, containerization, and multi-cloud deployment (GCP, AWS, Azure via Kubernetes / Docker).
• Debug complex, cross-layer issues spanning query planning, distributed execution, memory management, and I/O.
• Partner with US-based engineering leads on design reviews, architectural decisions, and roadmap execution.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with deep understanding of OOP, systems design, memory management, and concurrency. Candidates strong in both are especially valued.
• SQL & Data: Advanced SQL skills and strong understanding of query execution internals — planning, optimization, and operator implementation.
• Data processing systems experience: Demonstrated experience building or extending data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 5+ years in backend/systems software engineering, with a track record of owning significant components.
• CI/CD & DevOps: Solid experience with Jenkins and modern engineering workflows.
• Containers & Orchestration: Strong working knowledge of Docker and Kubernetes.
• Cloud: Hands-on experience with at least one major cloud (GCP, AWS, or Azure); exposure to more than one is a strong plus.
• Version Control: Confident with Git / GitHub workflows and rigorous code review practices.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.
• Leadership: Prior experience mentoring engineers, leading technical designs, or owning components end-to-end.

Desired Skills

• Deep experience with Apache Arrow (columnar in-memory format).
• Hands-on experience with Apache Calcite (SQL parsing, planning, optimization framework).
• Experience with Gandiva or LLVM-based expression compilation and code generation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Deep familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Deep understanding of query planning, optimization (cost-based, rule-based), and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Track record of performance optimization at the systems level — profiling, vectorization, cache/memory-conscious design.
• Prior experience contributing to open-source data infrastructure projects.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

Level: Middle Engagement: Long-term contract Location: Europe (EU / EEA / UK), remote Working hours: EU business hours, shifted 2–3 hours later to ensure daily overlap with US West Coast (PST/PDT) mornings

About the Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Middle-level Software Engineer to work on the core query engine of a large-scale distributed data platform. You will develop features across query planning, optimization, and execution, contribute to performance-critical components, and help evolve the platform's ability to process massive analytical workloads across heterogeneous data sources.

This is a systems-level, backend engineering role focused on distributed data processing internals — not application development or CRUD services.

Responsibilities

• Develop and maintain features across the query engine — planning, optimization, execution, and data access layers.
• Write high-quality, performance-conscious code in Java and/or C++.
• Work with SQL semantics, query plans, and execution operators over large-scale distributed data.
• Integrate with columnar formats, open table formats, and connectivity drivers used across the platform.
• Contribute to CI/CD pipelines and automated testing — participate in build, test, and release workflows in Jenkins.
• Deploy and validate work in Kubernetes (GKE / EKS / AKS) across GCP, AWS, and Azure using Docker.
• Debug complex issues spanning query planning, distributed execution, memory management, and I/O.
• Collaborate closely with US-based engineering teams on design reviews, code reviews, and technical decisions.

Required Qualifications

• Education: B.S. or M.S. in Computer Science, Computer Engineering, or a related technical field.
• Programming: Strong proficiency in Java or C++, with solid OOP and software design fundamentals. Candidates comfortable with both are especially valued.
• SQL & Data: Strong SQL skills and solid understanding of relational and analytical data systems, including query execution concepts.
• Data processing systems experience: Hands-on experience with data processing systems — query engines, distributed databases, ETL/ELT frameworks, or analytical platforms.
• Engineering experience: 3+ years in backend/systems software engineering.
• CI/CD & DevOps basics: Practical experience with Jenkins pipelines and modern development workflows.
• Containers: Working knowledge of Docker and basic Kubernetes (running workloads, debugging pods, kubectl fluency).
• Cloud: Comfortable operating in at least one major cloud (GCP, AWS, or Azure).
• Version Control: Confident with Git / GitHub workflows.
• English: Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team.
• Availability: Able to work EU hours with a 2–3 hour shift toward US West Coast time to ensure daily overlap with the client team.

Desired Skills

• Experience with Apache Arrow (columnar in-memory format).
• Familiarity with Apache Calcite (SQL parsing, planning, optimization framework).
• Exposure to Gandiva or LLVM-based expression compilation.
• Experience with open table formats — Apache Iceberg, Delta Lake, or Hudi.
• Familiarity with distributed computing frameworks (e.g., Apache Spark, Kafka) and MPP SQL query engines (e.g., Presto, Trino, or similar).
• Understanding of query planning, optimization, and execution internals.
• Experience with data connectivity drivers: JDBC, ODBC, Arrow Flight.
• Kubernetes on managed services (GKE / EKS / AKS) and multi-cloud exposure.
• IaC tools such as Terraform.
• Experience with performance profiling and optimization of latency-sensitive systems.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK.
  Please note: We can consider only candidates currently residing in the EU, EEA, or the UK

About the Role:

We are looking for an experienced Senior Data Engineer to join our team and help build scalable, secure, and high-performance data platforms. In this role, you will work closely with Data Architects, Engineers, Analysts, DevOps specialists, and Data Scientists to design, develop, and optimize modern cloud-based data ecosystems.

This is a full-time remote position for a senior-level professional who can commit 40 hours per week and take ownership of complex data engineering initiatives.

🔹 Responsibilities:

As a Senior Data Engineer, you will:

* Collaborate with Data Architects on designing and implementing data solutions across Azure, AWS, or IBM Cloud environments

* Build, maintain, and optimize modern data ecosystems and data pipelines

* Develop and support data ingestion, transformation, and processing solutions

* Work closely with cross-functional teams, including Data Engineers, Analysts, DevOps Engineers, and Data Scientists

* Implement security best practices to ensure the reliability and protection of cloud infrastructure and data processes

* Apply modern engineering principles and methodologies to support business growth and innovation

* Identify opportunities to improve data quality, reliability, scalability, efficiency, and overall platform performance

* Optimize data solutions to balance performance, maintainability, and cost-effectiveness

* Design and execute unit, system, and integration testing strategies

* Contribute to continuous improvement initiatives and engineering best practices

🔹 Requirements:

* Strong commercial experience as a Data Engineer

* Advanced proficiency in Python for data processing, transformation, and analysis

* Strong expertise in SQL, including query optimization and database performance tuning

* Hands-on experience with Azure and/or AWS data platforms and services

* Experience designing and maintaining scalable cloud-based data solutions

* Solid understanding of data engineering best practices, data modeling, and ETL/ELT processes

* Experience with software development lifecycle methodologies and Agile environments

Nice to Have:

* Experience with IBM Cloud data services

* Knowledge of data governance and cloud security practices

* Experience working in enterprise-scale data environments

🌍 What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production. 

A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement. 

What you’ll do: 

• Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. 
• Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. 
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. 
• Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models. 

What you’ll bring: 

Core (required): 

• Solid background in machine/deep learning, with 4+ years of experience. 
• Strong Python skills and experience working in Linux environments. 
• Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. 
• Experience with MLOps pipelines and serving/deploying models in production. 
• Experience optimizing models for inference, including GPU acceleration. 
• Experience with Docker, gRPC, and serverless / micro-services architectures on cloud infrastructure (AWS/GCP/Azure). 
• Experience with real-time / streaming systems and low-latency processing (e.g. streaming pipelines, live sessions). 

Nice to have (secondary / optional): 

• Experience building and productizing agentic flows and AI-driven solutions (1+ year). 
• Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. 
• Prior ASR / speech experience — not required; willingness to learn this domain is what matters most. 

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.

Dash Financial Technologies is a leading trading technology provider to the institutional trading community. With a suite of highly customizable tools, Dash designs and delivers intelligent, high performance solutions in four product categories: Trading Technologies, Execution Services, Analytics and Regulatory Technologies. With a relentless focus on transparency, performance and customization, Dash Financial Technologies caters to institutions that require increasingly specialized, complex and adaptable tools to exceed their goals surrounding best execution

We are looking for a skilled Business Analyst, ideally with experience in Capital Markets domain, as a ramp-up of our BA capacity on a modern order management system project. 

 

Requirements
o You have a technical background
o You have a passion for great, structured documentation and the benefits of knowledge management.
o You communicate clearly and precisely, leading others and transferring knowledge efficiently.
o You form strong, honest, and mutually respectful relationships with the key stakeholders

Desirable
o You have experience working with asset classes such as US Equities and Equity/Index Options.
o You have a good understanding of order management specifics particularly in the trading systems
o You are familiar with the FIX Protocol

Responsibilities
o Play the role of Business/System Analyst
o Work closely with the client to ensure requirements are captured, the scope is controlled, and expectations are met
o Work closely with the development team to do the entire system design
o Participate and facilitate workshops, stakeholder interviews, UX design sessions, solution planning & review meeting, etc.
o Specification of new functionality across the frontend and backend components
o Ongoing improvement of knowledge through better documentation and knowledge management infrastructure
o Play a proactive role in proposing new processes, tools & approaches
o Assist in project planning, quality control, and user acceptance testing
o Help investigate complex functional software issues, assist in root cause analysis, and establish a solution
o Identify and manage risks and flag major issues early

We are offering You 

• Remote work   
• Flexible working hours 
• All necessary equipment (laptop,monitors. etc.) 

📍 Location: Remote

🤝 Engagement: Full-time, long-term project for an international product client

💬 English: B2+

🎯 Level: Senior
 

About the Opportunity

We are looking for a Senior Web Scraping / Data Collection Engineer to join an international product project.

The project is already in development. The client is currently strengthening the data collection / web scraping direction and is looking for an engineer who can take ownership of the existing scraping work and continue developing it.

The main goal is to build a modern and scalable data collection system capable of extracting structured data from various community, hobbyist, and other public websites.

The system should primarily collect structured information about locations, including:

• Name
• Address
• Additional information available on the source
• Sentiment and user opinions

The client plans to use Crawl4AI together with LLMs to handle complex and dynamic content and enable intelligent data extraction.

What You'll Be Doing

• Develop custom scrapers using Crawl4AI.
• Extract structured data from various websites.
• Work with complex and dynamic web content.
• Implement advanced extraction strategies using Pydantic schemas, CSS selectors, and LLM-based parsing.
• Produce structured JSON / Markdown data optimized for further LLM processing.
• Extract basic location data such as names and addresses.
• Extract all available information about locations when additional data is provided by the source.
• Develop approaches for extracting sentiment from user opinions and discussions.
• Transform different opinions about a location into structured data that can be used for further processing and analytics.
• Work with different types of sources, including:
  • Community websites
  • Hobbyist websites
  • Blogs
  • Social media communities and groups
• Work with websites using sophisticated access restrictions, including age gates, CAPTCHAs, and IP rate limits.
• Use session persistence and browser fingerprinting to improve scraping success rates on challenging sources.
• Deliver clean and deduplicated data.
• Produce results in CSV or database-ready formats.
• Optionally contribute to a web interface that allows users to:
  • Enter URLs
  • Configure scraping settings
  • Adjust stealth mode
  • Set crawl depth
  • Add extraction instructions
  • Monitor scraping results

Data Structure

At a basic level, the system should be able to return location data in a simple structured format:

[

 {

   "name": "place1",

   "address": "address1"

 },

 {

   "name": "place2",

   "address": "address2"

 }

]

If a source contains more information, the system should be able to return additional fields in a consistent JSON format.

The system should also support extracting sentiment-related information.

For example, if 6 people mention that they loved a location, 2 consider it average, and 2 disliked it, this information should be structured in a way that can be used for further processing and analytics.

The exact sentiment format can be flexible, but consistent JSON is preferred.

What We're Looking For

• Commercial experience in Web Scraping / Web Crawling / Data Extraction.
• Strong Python skills.
• Hands-on experience working with dynamic and complex websites.
• Experience with browser automation.
• Good understanding of HTML / DOM and CSS selectors.
• Experience developing custom scrapers.
• Experience working with structured data and JSON.
• Experience with Pydantic or similar schema-based approaches.
• Understanding of LLM-based data extraction.
• Experience with session persistence and browser fingerprinting.
• Understanding of CAPTCHA, age gates, and IP rate limits.
• Ability to independently understand an existing scraping solution and continue developing it.
• English B2+.

Nice to Have

• Practical experience with Crawl4AI.
• Experience integrating Crawl4AI with LLMs.
• Experience with Playwright, Selenium, or similar tools.
• Experience with LLM-based parsing / information extraction.
• Experience with sentiment analysis / NLP.
• Experience collecting data from social media communities, blogs, and other user-generated sources.
• Experience building lightweight web interfaces for managing scraping jobs.

Who You Are

We are looking for an engineer who can independently take ownership of the scraping direction, understand the existing solution, and continue developing it.

It is important to be able not only to crawl pages, but to extract high-quality, structured, and usable data from them.

Strong practical experience with dynamic websites, browser automation, complex scraping scenarios, and structured data extraction is especially important.

What We Offer

• 🌍  Remote work.
• 📄  Full-time, long-term project.
• 🚀 Work on an existing international product.
• 🧠 Opportunity to take ownership of a dedicated technical direction.
• 💼 Work with Crawl4AI, LLMs, and modern data extraction approaches.
• 🤝 Direct collaboration with the client team.
• 📈 Opportunity to influence the technical solution and further development of the data collection system.

Hiring Process

1. Recruiter Screening

2. Client Interview (A technical interview with the client team focused on your practical experience, approach to complex scraping challenges, work with dynamic websites, and structured data extraction)

3. Offer 🎉

We’re looking for a Data Engineer to improve our data infrastructure and integration workflows.

This role is a great fit for someone who can quickly step into an existing environment, bring strong technical expertise, and help us build reliable, scalable solutions with a practical hands-on approach.

Responsibility:

• Design and build data templates for integration workflows
• Optimize and improve existing data pipelines
• Ensure smooth and reliable integration across SaaS systems

Requements:

• Commercial experience as a Data Engineer
• Python skills for data engineering tasks
• Understanding of building efficient, scalable, and maintainable data pipelines

Would be a plus:

• Experience with ETL / ELT

• Experience with cloud-based data platforms and modern data stack

   

Required languages

EnglishB2 - Upper Intermediate

An international energy trading company is looking for an AI Adoption & Enablement Lead to work remotely.

The team develops digital products at the intersection of energy trading and technology, helping shape the market in real time.

Operating across 23 countries with offices in Switzerland, Croatia, the Netherlands, and Ukraine, our 75-person team drives massive market impact. In 2024 alone, we managed 122.6+ billion kWh within the largest private balancing group, traded 34.4+ billion kWh of electricity, and handled 1.8 billion m³ of gas.

Requirements: experience in systems analysis, participation in transformation projects or systems integration, and hands-on experience with AI tools.

Nice to have: experience implementing AI tools within business processes, as well as experience in fintech or trading projects.

What we offer: 100% remote work, flexible schedule, long-term B2B contract, corporate hardware, 20 working days of paid vacation, covered sick leaves, and a highly influential role shaping the company's AI architecture.

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.

Powering Growth from the Core — this is the key mission laid under RedCore’s strong foundation. This is how we consistently stay ahead: by evolving and creating scalable solutions, while remaining committed to open and transparent communication with our partners.

We’re looking for a sharp and driven Senior Data Analyst to join our team!

Requirements:

• 4+ years of experience in product or data analytics;
• Strong experience with data visualization tools (preferably Tableau) — ability to design clear, insightful, and visually appealing dashboards;
• Excellent knowledge of SQL — writing complex queries, optimizing performance, and working with large datasets;
• Understanding of ETL processes and data modeling principles;
• Curiosity and proactive attitude — you love digging into data, finding patterns, and suggesting improvements.

Will be plus

• Experience in iGaming industry.

Responsibilities:

• Build and maintain Tableau dashboards for key product and business metrics (user engagement, retention, conversion, revenue, etc.);
• Write and optimize SQL queries to extract, transform, and structure data from multiple sources;
• Conduct deep-dive product analyses to uncover trends, user behaviors, and growth opportunities;
• Continuously improve data quality, performance of dashboards, and analytical infrastructure.

Our benefits to you:

• 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;
• Other benefits could be added based on your location.

20-30 hours per week

On behalf of our Client, Mobilunity is looking for a Data & Analytics Support Specialist.

You will join a team supporting data-driven decision-making through accurate reporting, dashboards, data validation, and business analysis.

The role is focused on ensuring that business and project teams have reliable, understandable, and up-to-date data. You will work with reporting tools, databases, and analytical datasets, investigate data inconsistencies, support ad-hoc requests, and help stakeholders understand key business metrics.

This is a part-time opportunity of 20–30 hours per week, making it a good fit for a data professional who enjoys working with reporting, analytics, and data quality in a flexible environment.

What we’re looking for:

We need a data-oriented professional who is comfortable working with reports and datasets, validating information, investigating inconsistencies, and supporting business users with data-related requests.

The ideal candidate:

• has a structured and analytical approach to working with data;
• is attentive to data accuracy and consistency;
• is comfortable working with SQL and reporting tools;
• can independently investigate data issues and identify trends or anomalies;
• understands KPIs and basic analytical concepts;
• can communicate data findings clearly to non-technical stakeholders;
• is comfortable handling both regular reporting and ad-hoc analytical requests.

Responsibilities:

• Prepare and maintain regular reports and dashboards.
• Extract data from databases and analytics systems.
• Check data for accuracy, completeness, and inconsistencies.
• Support ad-hoc data requests from business and project teams.
• Create and update KPIs and analytical metrics.
• Help users interpret reports and data.
• Write basic SQL queries to retrieve and validate data.
• Perform data cleansing and validation.
• Maintain data definitions and documentation.
• Check data pipelines and integrations.
• Support data quality initiatives.
• Maintain datasets used for reporting and analytics.
• Identify trends, anomalies, and significant changes in business metrics.
• Compare performance against KPIs.
• Perform basic statistical analysis.
• Investigate the reasons behind changes in business metrics.
• Provide insights and recommendations based on data.

Requirements:

• Commercial experience in Data Analytics, Data Reporting, Business Intelligence, or a similar role.
• Good understanding of SQL and experience using SQL to retrieve and validate data.
• Hands-on experience with AWS QuickSight.
• Hands-on experience with AWS Athena.
• Advanced Excel skills.
• Experience creating and maintaining reports and dashboards.
• Understanding of KPIs and analytical metrics.
• Experience with data validation, cleansing, and quality checks.
• Strong analytical and problem-solving skills.
• Ability to identify trends, anomalies, and inconsistencies in data.
• Good communication skills and ability to explain data to business users.
• Experience working with PowerPoint for presenting data and insights.
• Experience working with Jira or similar project management tools.
• Good command of English.

Nice to have:

• Experience working with data pipelines and integrations.
• Experience with BI or data visualization tools other than AWS QuickSight.
• Experience with data quality initiatives.
• Experience working in a business or product environment.
• Basic knowledge of statistics and data analysis.
• Experience supporting cross-functional or international teams.

We are seeking a hands-on Senior DevSecOps Engineer with strong AWS and Azure experience to embed security directly into our engineering lifecycle. In this role, you will be the technical engine that automates compliance guardrails, integrates security tooling (SAST/DAST, EDR, Vulnerability Management) into CI/CD pipelines, and routes critical security telemetry to our SIEM. Your mission is to build the automated scaffolding that allows software delivery to move at high speed without compromising on enterprise security or governance.

Key Responsibilities

·  CI/CD Security Automation: Design, build, and maintain secure deployment pipelines (e.g., GitHub Actions, Azure DevOps, GitLab CI). Integrate automated vulnerability scanning, secret detection, and software supply chain security (SCA) seamlessly into the developer workflow.

·  Policy-as-Code & Guardrails: Write, test, and deploy automated policy guardrails using Infrastructure as Code (IaC) linting and scanning tools (e.g., Checkov, Tfsec, OPA/Rego) to catch misconfigurations before they reach production.

·  Security Product Deployment: Automate the baking of EDR agents, vulnerability scanners, and monitoring tools into base machine images (AMIs, Azure Golden Images) and containerized base environments.

·  Vulnerability & Remediation Pipelines: Operationalize vulnerability management by building automated workflows that ingest findings from cloud security tools, prioritize them based on risk, and route them to engineering backlogs (e.g., Jira tracking).

·  Logging & SIEM Integration: Configure and automate the pipeline delivery of application, container, and infrastructure logs to central logging repositories and SIEM systems for real-time threat hunting.

·  Developer Enablement: Serve as a bridge between Security and Engineering, providing developer-friendly remediation guidance and creating reusable, secure-by-default code templates (Terraform modules, Helm charts).

Required Skills & Qualifications

·  DevSecOps & CI/CD Pipelines: Deep, practical experience constructing and securing automated build/release pipelines at scale.

·  Multi-Cloud Platforms: Hands-on engineering experience configuring native security services and access controls in both AWS and Azure.

·  Infrastructure as Code (IaC): Advanced proficiency with Terraform or cloud-native tooling (Bicep, CloudFormation), focusing on modular design and immutable infrastructure.

·  Security Tooling Implementation: Direct experience implementing and maintaining security products across the lifecycle (e.g., SonarQube, Prisma Cloud, Wiz, Snyk, CrowdStrike, or Sentinel).

·  Container & Orchestration Security: Strong understanding of Kubernetes (EKS/AKS) security best practices, service meshes, and container runtime defense.

Preferred Certifications

·  Certified DevSecOps Professional (CDP) or Practical DevSecOps certification

·  AWS Certified Security – Specialty or Azure Security Engineer Associate

·  Certified Kubernetes Administrator (CKA) / Certified Kubernetes Security Specialist (CKS)...

Description

The Digital Health organization is technology team which focused on next generation Digital Health capabilities which deliver on the Medicine mission and vision to deliver Insight Driven Care. This role will operate within the Digital Health Applications & Interoperability subgroup of the broader Digital Health team, focused on patient engagement, care coordination, AI, healthcare analytics & interoperability amongst other advanced technologies which enhance our product portfolio with new services, while improving clinical & patient experiences.

The project is a cloud-based PaaS Ecosystem built with a privacy by design centric approach to provide a centralized cloud-based platform to store, classify, and control access to federated datasets in a scalable, secure, and efficient manner.

The ecosystem will allow Customer Operating Units (medical device departments) to store federated data sets of varying sizes and formats and control access to those data sets through Data steward(s). Source data sets can be exposed to qualified use cases and workflows through different project types.

The Healthcare Data Platform ecosystem will provide ML/AI project capabilities for streamlined development processes and a ML/AI workbench to enhance data exploration, wrangling, and model training.

OU’s: Currently, Nuero, Cardio, Diabetes is the OU that HDP data platform is working with, but there could be more OU’s coming up with requirements in future.

GL Role: is to work on the enhancement of current capabilities, including taking over the work that AWS proserve team is doing, and develop new requirements that will keep coming from different OU’s in the future.

Requirements

As a System Engineer within the Company Research & Systems Engineering team, you will have the opportunity to work on cloud-based solutions with a strong focus on AWS, Data Engineering, and scalable data platforms. You will collaborate with cross-functional engineering teams to design, develop, integrate, and maintain reliable cloud-native systems and data workflows.

In this role, you will contribute to building and evolving AWS-based architectures, data processing pipelines, and integrations across distributed systems. You will develop a strong understanding of end-to-end system architecture, data flows, infrastructure, and operational requirements, helping to drive technical implementation and delivery throughout the software development lifecycle.

You will work closely with software engineers, data engineers, architects, and other stakeholders to ensure that solutions are scalable, secure, maintainable, and aligned with both technical and business requirements.

• 3+ years of experience in System Engineering, Software Engineering, Cloud Engineering, Data Engineering, or a related technical role.
• Strong software development experience with Python.
• Hands-on experience designing, developing, or supporting solutions on AWS.
• Experience with data engineering concepts and technologies, including data ingestion, ETL/ELT, transformation, validation, and data processing pipelines.
• Strong SQL skills and experience working with relational and/or NoSQL databases.
• Experience with REST APIs, service integrations, and distributed application architectures.
• Understanding of cloud-native architecture principles and modern software development practices.
• Experience troubleshooting applications and distributed cloud systems and performing root cause analysis.
• Experience with Git and modern CI/CD development workflows.
• Strong analytical and problem-solving skills with the ability to understand complex systems and data flows.
• Ability to work effectively with software, data, cloud, and machine learning engineering teams.
• BA/BS in Computer Science, Software Engineering, Information Technology, or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Experience with AWS data services such as S3, Glue, Athena, EMR, or similar technologies.
• Experience with Amazon SageMaker and machine learning development or deployment workflows.
• Experience with Infrastructure as Code using AWS CloudFormation, Terraform, or AWS CDK.
• Experience with AWS monitoring and observability services such as CloudWatch and CloudTrail.
• Experience working in Agile/Scrum development environments.

Job responsibilities

• Work with engineering and cross-functional stakeholders to gather, analyze, clarify, and document business, functional, and non-functional requirements, translating them into clear system and technical requirements.
• Define system requirements, interfaces, data flows, integration requirements, acceptance criteria, and technical constraints for cloud-based software components, data platforms, and integrations.
• Maintain requirements throughout the development lifecycle, ensuring traceability between business needs, system requirements, technical design, implementation, and validation.
• Identify gaps, dependencies, assumptions, and potential technical risks in requirements and work with stakeholders to resolve them before and during implementation.
• Design and contribute to scalable AWS-based architectures supporting data ingestion, processing, transformation, storage, and distribution.
• Analyze data and system behavior to support architecture, implementation, performance, and product decisions.
• Collaborate with Data Engineering, Software Engineering, Cloud Engineering, DevOps, and Architecture teams to design and integrate end-to-end cloud solutions.
• Support operational monitoring, logging, alerting, and troubleshooting of cloud applications and data processing workflows.
• Contribute to system architecture and technical design discussions, including scalability, reliability, security, performance, and cost considerations.
• Participate in technical and requirements reviews to ensure solutions meet defined requirements, engineering standards, cloud best practices, and established software development processes.
• Support continuous improvement of cloud infrastructure, data pipelines, deployment processes, requirements management, and engineering practices throughout the software development lifecycle.

N-iX  is looking for an experienced Senior Data Scientist with a strong focus on AI Engineering. The role involves designing and delivering production-ready AI solutions for the insurance industry, with a particular emphasis on Agentic AI, LLMs, RAG pipelines, and Computer Vision.

Key Responsibilities:

• Design and develop autonomous AI agent systems for the insurance domain
• Build production-ready AI solutions using:
  • Multi-Agent Systems
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Computer Vision
• Research, evaluate, and implement state-of-the-art AI technologies
• Develop scalable AI products for international markets
• Collaborate with a team of Data Scientists and AI Engineers
• Take AI solutions from architecture and proof of concept through production deployment
• Participate in building proprietary AI models for the insurance industry

Required Skills:

• 5+ years of commercial experience as a Data Scientist / AI Engineer
• Strong Python development skills
• Hands-on experience with:
  • Machine Learning
  • Deep Learning
  • Generative AI
  • LLMs
  • RAG architectures
  • AI Agent frameworks
• Experience building production AI systems
• Solid software engineering background
• Experience with data analysis and AI product development
• Degree in Computer Science/Data Science/Mathematics/Physics/Engineering or equivalent technical background
• Upper-intermediate+ English level 
• Strong analytical thinking, proactive mindset
• Ability to design scalable AI solutions
• Ability to explain complex technical concepts
• Independent and structured way of working
• Team player

Nice to Have:

• Experience within the insurance industry
• German or Spanish language skills

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

* benefits package is not applicable for freelancers

Playtika is looking for a Data Scientist Expert — Production ML to join the Data & AI department

In this position you will join a multidisciplinary team focused on personalization using Reinforcement Learning methods. Over the last few years, we have built a real-time recommendation engine based on Bayesian Multi-Armed Bandits — including our open-source PyBandits library — serving millions of players across multiple studios and use-cases.

This is an applied research role, with impact measured in production. Your primary contribution will be advancing the mathematical and statistical foundations of our existing solutions: identifying limitations, deriving principled improvements, and owning those improvements all the way through to production. You will not be handed research problems from above — you will find them yourself, inside systems that are already running at scale.

Scaling here is fundamentally a mathematical problem: identifying better statistical methods, proving they hold under real-world constraints, and knowing exactly how far they deviate from the ideal. That’s what sets this role apart.

Responsibilities

Identify mathematical and statistical limitations in existing ML solutions and deliver provably correct, more efficient alternatives
Validate the correctness of scaled solutions — diagnosing where distributed execution or approximation invalidates prototype-level results, and redesigning accordingly
Own the full lifecycle of your improvements: from research and prototyping through production deployment and impact measurement
Drive the evolution and scalability of our personalization and recommendation systems to meet future business and technical requirements
Contribute to end-to-end data-driven research including problem definition, data collection, model development, evaluation, and deployment
Collaborate with cross-functional teams (engineers, BI, Product) to deploy solutions quickly and effectively
Mentor Data Scientists and ML Engineers, and serve as a technical reference on statistical and mathematical rigor across the organization

Qualifications

M.Sc or PhD in Computer Science, Mathematics, Statistics, Engineering or a related field
5+ years of relevant working experience, including significant production ML ownership
Demonstrated experience taking statistically sophisticated models from prototype to production and operating them successfully under real-world business constraints.
Experience with neural network architectures, including the ability to diagnose, interpret and debug their behavior in probabilistic or decision-making contexts (e.g. Bayesian Neural Networks, Neural Linear models)

Strong theoretical foundation in at least one of: Multi-Armed Bandits, Bayesian methods, online learning, recommendation systems, or related decision-making frameworks
Strong understanding of experimentation, causal inference and statistical evaluation of online decision systems.
Strong hands-on Python engineering skills, with the ability to design, implement, review, and maintain production-quality code, leveraging modern AI coding assistants (e.g., Claude, Cursor) to improve productivity and code quality
Proficiency in SQL
Clear written and verbal communication — able to explain statistical reasoning to non-technical stakeholders
Ability to operate autonomously and influence decisions across teams without direct authority.

Nice to have

Experience with probabilistic programming frameworks (e.g. PyMC or Numpyro)
Familiarity with MLOps tooling (experiment tracking, model serving, monitoring)
Familiarity with approximate inference methods (variational inference, MCMC)
Experience with PySpark
Experience in the Mobile Gaming industry