Jobs Data Science

Evowill is looking for a Junior Data Scientist who is passionate about data analysis, machine learning, and extracting insights from data, and eager to grow in a supportive and dynamic environment. We offer a clear path: starting with a hands-on internship and transitioning into a commercial project role — 100% of our juniors join real projects.

Requirements:

• Knowledge of Python
• SQL (MySQL / PostgreSQL)
• Basic understanding of Machine Learning (scikit-learn)
• Basic data analysis skills (Pandas, NumPy)
• Solid statistics foundations
• Git, GitHub/GitLab
• English: Intermediate
• Pet projects (data analysis / ML) 
• Fast learner, organized, responsible
   

Would be a plus:

• Quantitative Science (Math, physics, statistics) or Engineering with ML or modeling majors (3rd year or higher)
• Experience with statistical or numerical modeling or having participated in data related research teams
   

Internship Stage (3 months):

• Full-time, practical learning
• Pet projects, technical interview preparations, and soft skills training
• English Speaking Club
• Senior Developers mentors from Ukraine and Colombia
• Technologies: Core Data Analysis and Modeling, Python libraries, as well as learning to apply modern ML techniques to real-world data.

Project Stage:

• Join commercial projects as a Data Scientist
• Salary from $1000 with regular reviews
• Ongoing mentorship and technical support
• Optional English club and extra tech learning

Gamzix is a high-growth international licensed iGaming provider, creating high-performing games and scalable, cutting-edge solutions for the global market.
Our team of 150+ specialists operates globally, with Warsaw as our main hub office. We are driven by continuous improvement and a people-first culture where we communicate openly, win together, and truly enjoy the game we’re building.
We operate under an MGA B2B Critical Supply License and certifications from iTechLabs and GLI, ensuring our products meet high standards of quality, compliance, and performance across markets.

We are looking for a Senior Mathematician to create, calibrate, deeply tune, and validate mathematical models for our slot games. We are scaling our mathematical department to transition to a dedicated structure, assigning one dedicated mathematician to each of our game streams. 

Responsibilities

• Develop and design mathematical models for slot games from initial concept to release
• Collaborate closely with Game Producers to refine, balance, and tune game concepts
• Validate, simulate (alongside simulation developers), and sign off on mathematical models to ensure they perform strictly as intended
• Troubleshoot with engineers on the precise technical implementation and integration of math models
• Maintain structured documentation and records of game math files, configurations, and simulation benchmarks
• Provide expert math support and clear explanations for game designers, engineers, compliance, and other internal teams
• Deliver early feedback and predictions on player engagement based on the game's mathematical profile
• Design and propose original features and mathematical solutions for diverse game mechanics
• Analyze BI performance data of live games to continuously tune and optimize mechanics based on real metrics
• Mentor and support junior team members, guiding them through technical decisions during math creation

Requirements

• 2–3 years of practical commercial experience creating mathematical models specifically for slot games (experience in game providers, dedicated slot studios, or outsource)
• Deep knowledge of probability theory, combinatorics, RTP calculation, volatility, and mechanics balancing
• Proficiency in specialized mathematical modeling tools, simulation software, and working with math files
• Hands-on experience with Python and/or C++ for calculations and simulations
• Experience working with BI analytics to evaluate product performance
• Perfectionism and strong attention to detail: a drive to bring models to perfection, deeply tune, and polish the math
• High level of autonomy with the ability to conduct calculations and manage your workflow independently without micromanagement
• Solid communication skills for regular dialogue with the Game Producer and the wider team

Benefits

• 7-hour working day, 10:00 AM—6:00 PM, including a lunch break
• A-class office in Mokotów, Warsaw
• Competitive salary in the IT field, with taxes paid
• 10 days of paid sick leave
• 28 days of paid vacation: 18 days plus 10 additional days separately
• Paid state holidays
• Medical insurance
• Courses and training reimbursement
• Referral bonus for bringing talented people to the team
• Corporate English courses: business or general English, with morning and evening schedules
• People-oriented company with a focus on work-life balance
• Open and friendly communication
• Corporate team-building events and activities

Please note that feedback on your application will be provided within two weeks if a positive decision is made regarding your candidacy.

*This is 4-hour role, for a 20-hour working week that requires coverage within the 08:00 - 17:00 CET timezone, Mon-Fri

Role purpose

Act as the Data Steward for M&S Cockpit, serving as a key liaison between business stakeholders, data providers, and technical teams for one of the biggest food and beverages company - a long-temr customer of ours. The role focuses on understanding business requirements, coordinating data validation activities, ensuring data quality and consistency, and resolving discrepancies across sources, mappings, and reporting outputs. It combines stakeholder management, business analysis, and data governance, ensuring that datasets are reliable, aligned with business expectations, and ready for downstream consumption.

The Data Engineering team builds and maintains pipelines, while mappings and configurations determine cell/model scope; Snowflake extraction jobs run SQL through Databricks, with Blob Storage, validation, Medallion transformations, Power BI review, and Gold delivery to Ekimetrics. The operating model also requires end-to-end triage across MDFA, CDF, WPP, Data Foundation, Redmill, and market stakeholders rather than treating every discrepancy as a coding defect.

Key responsibilities

• Act as a Data Steward for the M&S Cockpit, ensuring data quality, consistency, completeness, and alignment with business requirements.
• Serve as a key point of contact for business stakeholders, including Product, CMIA/markets, WPP/MDFA, CDF, data providers, and Ekimetrics, to understand data needs, clarify expectations, and coordinate priorities.
• Facilitate discussions with stakeholders to identify data issues, gather requirements, agree on definitions, and translate business needs into actionable tasks for technical teams.
• Coordinate data validation activities, ensuring that new data sources, market updates, and reporting outputs meet agreed business expectations.
• Monitor and investigate data-quality issues, including missing data, inconsistencies, anomalies, incorrect mappings, taxonomy differences, and reporting discrepancies.
• Collaborate with Data Engineers and other technical teams to resolve data issues, improve data flows, and ensure reliable delivery of information.
• Maintain and improve data definitions, business rules, mapping documentation, and data governance standards across multiple sources and markets.
• Support stakeholder communication by providing regular updates on data quality, issue resolution, delivery readiness, and outstanding risks.
• Identify opportunities to improve data governance, streamline validation processes, and strengthen collaboration between business and technical teams.
• Recommend practical automation, reliability, performance, and maintainability improvements while respecting platform standards and business-validation ownership.

The role should coordinate and technically enable business validation, not replace the data owner. 

Must-have technical competencies

• Experience as a Project Manager, Business Analyst, Data Steward, or similar role, preferably in data-driven projects or large corporate environments.
• Strong understanding of data management, data quality, data validation, and data governance principles.
• Proven experience working with multiple business stakeholders, gathering requirements, managing expectations, coordinating activities, and driving issues to resolution.
• Ability to translate business requirements into data definitions, validation rules, mappings, and actionable tasks for technical teams.
• Strong analytical and problem-solving skills, including investigating data discrepancies, identifying root causes, and coordinating corrective actions.
• Experience coordinating cross-functional teams, including business users, Data Engineers, external data providers, and reporting teams.
• Excellent communication, stakeholder management, and organizational skills, with the ability to explain complex data issues to non-technical audiences.
• Ability to work independently, prioritize competing requests, maintain documentation, and ensure timely delivery of business-ready datasets.
• Good understanding of data pipelines, ETL processes, SQL, databases, and reporting tools is a plus

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

*not applicable for freelancers

We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

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

*not applicable for freelancers

About Keymakr
We take care of all aspects of Data Set Preparation, Annotation, and Labeling for video and images.
We adhere to a personalized approach, providing a tailored solution for each of our clients.
Our brilliant in-house R&D team personalizes the annotation tools for each client based on their needs, so we can successfully tackle even the most complicated requirements the client might have.
Use cases: Self-driving cars, Facial Recognition & Security, Medical Annotations, Drones, Robotics, and any industry you can think of.

We are seeking a Solution Engineer to develop technical solutions for data annotation projects, implement AI tools, and automate workflows.

In this role, you will work with Computer Vision and NLP/LLM technologies, helping to improve the efficiency, quality, and profitability of projects.

Key Responsibilities

1. Technical support for POCs: setting up tools and workflows, validating data and results, identifying and resolving technical issues during pilot project launches.
2. Research and implementation of AI tools: finding and testing data annotation platforms, setting up pre-annotation and model-assisted labeling, working with SAM and YOLO models, and evaluating their effectiveness.
3. Development of AI solutions and automation: creating scripts, bots, and small applications using Claude, ChatGPT, and similar AI tools; automating data processing, validation, and conversion; integrating services via API; supporting the Rocket.Chat bot. Technical project support: solving non-standard problems in 2D/3D Computer Vision, video annotation, and NLP/LLM, configuring platforms, and assisting project teams.
4. Testing and optimization: verifying solution functionality, finding errors, preparing bug reports and requirements for Keylabs improvements, and finding ways to reduce labeling time and costs.
5. Documentation and training: preparing technical instructions, developing a knowledge base, and training colleagues on new tools and processes.

What we expect

1. Understanding of data labeling processes for Computer Vision (2D/3D) and NLP/LLM.
2. Analytical thinking, initiative, and the ability to independently learn new technologies and tools.
3. Practical experience solving problems using Claude, ChatGPT, or similar AI services.
   Basic knowledge of Python and API principles.
4. Understanding of JSON, XML, CSV, COCO, and YOLO data formats.
5. Understanding of pre-annotation and model-assisted labeling principles.
6. Software testing skills, error detection, and result validation.
7. Experience with data annotation platforms such as Keylabs, CVAT, Labelbox, SuperAnnotate, or similar solutions.
8. Ability to structure information, create technical documentation, and clearly describe technical issues.

Important: Commercial development experience and the ability to write code from scratch are not required. Logical thinking, confidence in using AI tools, the ability to independently understand technical problems, and bring solutions to a working state are key.

Experience with fine-tuning models is an advantage.

1. Proficiency in Docker.
2. Experience with LiDAR and point clouds.
3. Prompt engineering and LLM response validation skills.
4. English proficiency sufficient for reading technical documentation and communicating with international clients.

Working Conditions

1. Salary: UAH 30,000 gross.
2. Fully remote work.
3. Flexible schedule.
4. Opportunity to work with modern AI tools and participate in the development of technical solutions for real-world projects.
5. Opportunity for professional development in AI, Computer Vision, NLP/LLM, and process automation.

We look forward to welcoming you to our team!

N-iX is for a Middle Applied Scientist to join our team and improve how customers discover, evaluate, and select content for AI training datasets. You will own scoped scientific projects from problem framing through recommendation, while helping shape broader methods and standards with senior and principal data science colleagues. Working with product and engineering partners, you will turn evaluation results and experimental evidence into improvements to the Data Licensing platform.

This role is well suited to someone who has applied statistical and machine-learning methods in production and is ready to take greater ownership of product-facing scientific work.
 

Our customer is a technology company that powers one of the world's largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organizations of all sizes. In this role, you will be working with highly motivated and talented data scientists and engineers who are primarily focused on developing next-generation AI/ML systems that transform the way people find content they enjoy.
 

Responsibilities:

• Partner with senior and principal data scientists to improve dataset discovery, qualification, and selection by evaluating and enhancing retrieval, classification, filtering, and ranking approaches
• Develop and apply evaluation and sampling methods to measure dataset relevance, coverage, diversity, composition, and representativeness.
• Evaluate automated dataset-curation workflows, using structured error analysis to assess interpretation, selection quality, and failure modes and recommend improvements.
• Design and analyse experiments using offline evaluation and product telemetry to recommend improvements to curation quality, workflow performance, and customer experience.
   

Requirements:

• 4+ years of commercial experience in data science, applied science, machine learning, or a related field.
• Strong grounding in statistics, experimental design, and quantitative problem-solving.
• Experience evaluating search, recommendation, ranking, and similar machine-learning systems.
• Experience taking experiments from problem framing and metric definition through analysis and recommendation.
• Proficiency in Python and SQL and experience working with large datasets.
• Practical experience applying several relevant techniques, such as sampling, clustering, classification, optimisation, uncertainty estimation, or Bayesian methods.
• Experience using structured error analysis to identify opportunities to improve model or platform performance.
• Strong communication skills and experience working with product and engineering partners.
• Ability to innovate and identify new approaches to improve current practices.
• English level - upper-intermediate or higher
• Working experience AWS and/or GCP

Nice to have:

• Experience with embedding models, semantic search, information retrieval, and multimodal content.
• Experience evaluating LLM-based or agentic workflows.
• Understanding of annotation workflows, from human labelling to model-assisted and VLM-based annotation.
• Experience estimating full-population quality from representative samples.

Project Description:

Join our Development Centre in Bucharest and become a member of our open-minded, progressive and professional team. In this role you will be working for one of our world-famous clients.

The Chief Security Office (CSO) of our client comprises the Chief Information Security Office (CISO) and the Corporate Security unit. The CISO organization guarantees information security for our client.

The role resides inside the Cyber Hygiene Engineering team within CSO. The team is responsible for developing and maintaining security solutions that improve the organization's security posture through automation, cloud security, vulnerability management, and application security.

We are looking for a Python-focused AI and data science engineer to help design, build, and improve practical AI automation workflows. This role is suited for someone who can combine strong software engineering discipline with applied machine learning, data analysis, and LLM-based tooling.

On top of attractive salary and benefits package, Luxoft will invest into your professional training, and allow you to grow your professional career.

Responsibilities:

• 4-5 years+ of experience

• Design, build, and maintain Python-based AI workflows, evaluation harnesses, and automation tools.

• Work with LLMs, AI agents, prompt pipelines, embeddings, and retrieval-augmented generation.

• Analyze structured and unstructured data to support automation, decision-making, and model evaluation.

• Create datasets, validation sets, benchmarks, and evaluation metrics for AI-assisted workflows.

• Integrate AI tools with existing business processes, internal data sources, and developer workflows.

• Improve reliability, observability, and repeatability of AI outputs.

• Document technical decisions, workflows, and assumptions clearly.

Mandatory Skills Description:

• Strong Python experience, including clean scripting, packaging, testing, and data processing.

• Practical experience using LLM APIs, AI agents, prompt engineering, or AI automation frameworks.

• Ability to design experiments, evaluate model outputs, and interpret results.

• Familiarity with notebooks, Git, virtual environments, and reproducible development workflows.

• Good software engineering habits, including tests, readable code, version control, documentation, and maintainability.

• Ability to turn ambiguous business or workflow problems into concrete technical prototypes.

Nice-to-Have Skills Description:

• Experience in a multinational environment would be a plus

ZentixSoft is looking for a Hands-on Technical Lead / Data Architect! 🚀

Format: Full-Time Outstaffing, 13-week engagement (First 3 weeks 100% on-site in Riyadh, followed by a hybrid schedule) with long-term extension options.

Location: Riyadh, Saudi Arabia (Open to candidates in KSA or willing to relocate).
 

🧩 Responsibilities:

• Architecture & Hands-On Engineering: Design HLD/LLD for Lakehouse architectures (raw, standardized, curated layers), Customer 360 target data models, and source-to-target mappings from Oracle Data Warehouses and Data Lakes while writing production SQL and Python code.
• GCP Infrastructure & Pipeline Ownership: Build and review pipelines using Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Cloud Run/GKE, Airflow, dbt).
• Identity Resolution & Quality: Implement deterministic/probabilistic matching rules, data quality frameworks, reconciliation, and lineage metadata.
• BI & Enterprise Integration: Build Power BI semantic models with Row-Level/Object-Level security, embed reporting into Dynamics 365, and set up AI-ready foundations (Vertex AI / BigQuery ML).
• Security & Compliance: Enforce security by design, encryption, audit logging, and KSA PDPL data residency standards.
   

🎓 Our Perfect Match (Requirements):

• Data Engineering & Architecture: 10+ years in Data Engineering/Architecture, with 3+ years of hands-on experience on Google Cloud Platform (GCP).
• Production Tooling: Proven production experience with BigQuery, Airflow, dbt, SQL, and Python.
• Domain Expertise: Strong background in Insurance or Banking data domains (policies, claims, customers, providers).
• Team Leadership: Experience leading technical teams of 6–8 engineers while maintaining hands-on contribution.
• On-Site Presence: Available for the first 3 weeks 100% on-site in Riyadh, transitioning to a hybrid setup afterwards.
   

➕ Nice to Have:

• Experience with restricted-data zones (e.g., medical data regulations).
• Hands-on knowledge of BigQuery ML, Gemini, or Vertex AI.
   

📍 Project Details:

⏳ Duration: 13 weeks + long-term extension.

📍 Location: Hybrid Riyadh (First 3 weeks full-time on-site).

Key responsibilities

• Own end-to-end solution architecture for data, analytics, and AI use cases, with accountability for design quality, security, scalability, supportability, and cost.
• Translate business needs into practical technical designs, target architectures, integration patterns, and delivery-ready implementation guidance.
• Lead by example through hands-on prototyping, architecture reviews, troubleshooting, code/design reviews, and technical support for delivery teams.
• Ensure security, governance, compliance, and operational readiness are built into solutions from design through production deployment.

Must have

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of IT experience, including 5+ years in senior solution architecture roles for enterprise data, analytics, and AI platforms.
• 5+ years strong hands-on experience with Azure-based data platforms, including Azure Data Factory, Databricks, data lake architectures, SQL, and dimensional data modeling, with the ability to build practical end-to-end solution designs.
• Strong experience with enterprise security, governance, and compliance, and the ability to work effectively with enterprise architects and guiding or regulatory functions to ensure solutions meet organizational standards and control requirements.
• Enterprise AI enablement experience: designing solutions with Azure OpenAI and retrieval-augmented (RAG) patterns.
• BI/analytics architecture experience with Power BI or a similar enterprise BI technology.

Advantages

• Deep hands-on expertise in Power BI architecture, including semantic models, DAX, Power Query, workspace strategy, governance, performance optimization, and enterprise reporting patterns.
• Experience with Microsoft-first AI platforms and services such as Azure AI Foundry, Copilot Studio, Azure AI Search, Semantic Kernel, Prompt Flow, and enterprise AI governance patterns.
• Experience with Microsoft Fabric, Azure DevOps, GitHub Enterprise, and CI/CD for Data or AI solutions.
• Experience with Microsoft security and governance services such as Microsoft Entra, Purview, and Key Vault.
• Experience in life sciences, pharmaceuticals, or other regulated industries.
• Relevant Microsoft certifications in Azure, Power BI, data, or AI architecture.

Key skills

• Hands-on technical leadership with a clear lead-by-example mindset.
• Strong architecture judgment across data, analytics, AI, integration, security, and non-functional requirements.
• Proven ability to own solution architecture end to end: shape target designs, validate them through prototyping or proof of concept where needed, guide delivery teams through implementation, and provide technical oversight through design reviews and production readiness checks.
• Ability to translate business problems into practical, delivery-ready technical solutions.
• Strong troubleshooting, decision-making, estimation, and risk management capability.
• Comfort working across distributed teams and external suppliers in enterprise delivery environments.
• Excellent communication skills in English, with the ability to drive alignment across architects, delivery teams, business stakeholders, and enterprise control functions.

We are looking for a Senior AI/ML Engineer to design, develop, and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready machine learning and LLM-based solutions, from understanding business needs and exploring data to designing technical approaches, implementing solutions, and integrating them into Foundry workflows. You will work closely with data engineers, business analysts, and domain experts, contribute to technical decisions, and help establish best practices for building scalable and reliable AI solutions.

Key Responsibilities:

• Design and develop AI/ML solutions for predictive analytics, classification, forecasting, automation, and AI-assisted workflows within Palantir Foundry, leveraging Python, Ontology objects, pipelines, and workflows.
• Design, implement, evaluate, and optimize LLM/NLP and RAG solutions using Palantir AIP, including prompt engineering, embeddings, retrieval strategies, vector search, and text processing.
• Own the end-to-end lifecycle of AI solutions, from experimentation and model development to deployment, monitoring, and continuous improvement.
• Collaborate with data engineers to understand data sources, ensure data quality, and design efficient and scalable data processing approaches.
• Integrate AI solutions into production workflows and optimize them for accuracy, reliability, latency, scalability, and cost-efficiency.
• Contribute to technical architecture and design decisions, including model, framework, and tool selection; proactively identify technical risks, improvement opportunities and proactively propose solutions.
• Work with business and domain stakeholders to translate business needs into practical, scalable, and production-ready AI solutions, clearly communicating technical decisions and model limitations.
• Identify technical risks, limitations, and opportunities for improvement and proactively propose solutions.

Requirements:

• 4+ years of experience in machine learning, AI engineering, applied data science, or related fields.
• Strong Python skills and hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong practical experience with LLMs, NLP, or GenAI applications, including prompt engineering, embeddings, text processing, summarization, or similar use cases.
• Solid hands-on experience designing and implementing RAG architectures, vector databases, and retrieval strategies.
• Strong understanding of the ML lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Experience working with both structured and unstructured data, including tabular data, time series, text, and documents.
• Ability to independently analyze ambiguous problems, propose technical approaches, and drive solutions from concept to implementation.
• Strong communication skills, with the ability to explain AI concepts, technical decisions, and model behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to Have:

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)

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

*not applicable for freelancers

Dataforest are looking for a highly experienced Team Lead Data Science with a strong engineering and managerial background (10+ years in the domain). In this role, you will lead and scale our AI/Data Science practice, establish robust development processes, drive pre-sales and R&D activities, and effectively manage an engineering team of 8–10+ members.
 

 What you’ll do:

• Team Leadership & Management: Lead and grow the Data Science department (8–10+ people), perform 1-on-1s, technical assessments, and performance reviews.
• Architecture & Strategy: Define the AI/DS architecture and tech strategy, establish high-quality coding standards, and oversee code reviews.
• Business & Pre-sales: Collaborate closely with C-level executives (CEO/CTO) to shape development processes, lead pre-sale activities, and estimate complex AI projects for international clients.
• R&D & Solution Delivery: Drive complex AI projects from concept to production (High-Load systems, LLM/RAG solutions) and conduct R&D with cutting-edge technologies.
   

 You'll be a great fit if you have:

• 10+ years of total experience in Data Science, Machine Learning, Data Engineering, and Software Engineering.
• Management Experience: Proven track record of leading teams of 8+ engineers (Data Scientists, ML Engineers).
• AI & LLM Expertise: Deep practical knowledge of the modern AI stack: LLM, RAG, LangChain, LangGraph, and AI Agents.
• Core Tech Stack:
  • Mastery of Python, algorithms, and data structures.
  • Proven experience in building scalable ML/DS architectures and high-load production systems.
  • Solid understanding of MLOps, Docker, Kubernetes, and CI/CD pipelines.
• Business Analysis & Pre-sales: Demonstrated capability in project estimation, client communication, and translating complex business requirements into technical solutions.
• English: Upper-Intermediate (B2+) or higher for fluent communication with international clients.

We ensure your growth with:

• Great networking opportunities with international clients and challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leave;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team-building activities and corporate events.

We are looking for an experienced Quant Engineer to join our Trading Core and Risk Tech teams and take ownership of the mathematical models behind our trading and risk infrastructure. With billions in trading volume processed across our systems, accuracy, scalability, and model reliability are essential.

You will develop, backtest, and optimize the quantitative models powering our pricing engines, automated market-making strategies, risk management frameworks, including A/B/C-book optimization, and liquidation logic. Working closely with Core Product Managers and engineering teams, you will apply advanced mathematics, data analysis, and high-performance engineering to turn complex market data into scalable models and proprietary trading advantages.

Responsibilities

• Research, design, and prototype quantitative models for pricing, risk management, and market making
• Build and maintain robust backtesting frameworks to validate the performance and safety of models before production deployment
• Write clear, comprehensive mathematical and algorithmic specifications for Backend Engineers (Trading Core squads)
• Cross functional with the R&D and Trading Ops teams
• Conduct post-incident deep dives (e.g., after major market gaps or liquidations) to identify algorithm performance gaps and optimize them

Requirements

• 4+ years of experience as a Quant or Data Scientist
• Exceptional knowledge of probability theory, stochastic calculus, time-series analysis, and financial mathematics
• Advanced proficiency in Python (NumPy, Pandas, SciPy, SK-Learn, Statsmodels) for data analysis, modeling, and backtesting
• Experience with Machine Learning
• Deep understanding of market microstructure, order book dynamics, risk metrics (VaR, Expected Shortfall), and margin/liquidation mechanisms
• SQL skills and experience working with large-scale historical market data (tick data, order logs)
• Strong logical thinking, initiative, and well-developed communication skills

Will be a plus

• Experience in CFD, Crypto CEX, Prop Trading Firm, or Hedge Fund
• Degree (MSc or PhD preferred) in a highly quantitative field: Mathematics, Physics, Quantitative Finance, Statistics, or Computer Science
• Understanding of Asset pricing models (e.g., Black-Scholes, local volatility models, Greeks management)
• Knowledge of the MetaTrader platforms (MT4/MT5)
• Experience with AI (Claude.io, Copilot, Codex)

We offer

• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company’s approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better.

We are now looking for a hands-on Leader who can bridge the gap between advanced research and real-world product delivery. You will be the technical anchor for two streams: S&D (Service & Delivery), ensuring our clients get robust, profitable pricing recommendations, and R&D (Research & Development), guiding the strategy for next-gen algorithms.

What you will do

• Have clear vision and own the strategy of Data Science in the organization.
• Shape the technical roadmap based on business needs, team capacity, and long-term strategy.
• Gradually scale data science function with company growth. 
• Define the hiring profile, lead and mentor a cross-functional team of Data Scientists, and cultivate a high-performing R&D culture focused on scientific rigor and measurable business impact.
• Manage resources across both Delivery (S&D) and Research (R&D) squads.
• Act as the main bridge between R&D and S&D: translate business requirements into research tasks, and help the team adapt complex prototypes into stable, production-ready solutions.
• Architect client solutions by selecting the right models and assortment strategies to solve specific business problems using our existing stack.
• Serve as the quality gatekeeper for the team, conducting code reviews, verifying A/B test designs, and ensuring the team hits their Definition of Done (DoD).
• Drive key DS metrics such as research-to-production time, experiment velocity, and the overall quality of price recommendations.
• Communicate clearly with product managers, engineers, and occasionally clients to explain DS trade-offs, present results, and align on next steps.
• Confidently represent the company's technological expertise to investors and partners. You will clearly articulate the Data Science strategy, the core algorithms' defensibility, and the technical roadmap during high-stakes due diligence processes.
• Engage directly with customers' Data Science and Analytics teams (including PhD-level experts). You must be able to confidently explain our methodology, model assumptions, performance results, and address their most technical questions, serving as a critical differentiator during sales and pilot phases.
• Present complex model results, performance metrics, and strategic trade-offs to key stakeholders in a clear, concise, and business-focused manner.
• Support the sales and pre-sales process by building compelling technical narratives that demonstrate our value proposition and deep expertise in the pricing domain.
• Stay hands-on: dive into code and architecture when needed - whether it's designing a new experiment, fixing a critical issue in the delivery pipeline, or prototyping a new idea.

What you have

• 5+ years of experience in Data Science or a related field with a focus on delivering value to production.
• Strong Python and SQL skills, capable of writing modular and readable code for experiments and prototypes.
• Familiarity Databricks data platform and Apache Spark.
• General familiarity with Data Mesh approach and ability to leverage its best practices in collaboration with data engineers.
• Solid mathematical background, preferably in a Computer Science-related field.
• Proficiency in the scientific Python toolkit, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.
• Deep understanding of statistical testing methodologies, specifically A/B testing design.
• Familiarity with Time Series Forecasting approaches.
• At least 3 years of experience working with tabular and mixed (multimodal) data.
• Expertise in Causal Inference and background in Ecommerce/Retail are strong pluses.
• Upper-intermediate or higher level of English and strong public speaking skills.

Soft skills 

• You care not only about how the model works mathematically but what value it brings to the user and the business.
• Able to translate complex technical concepts into simple business language for stakeholders.
• Able to professionally and clearly communicate with PhD scientists on customer side during the sales process, pilot and rollout.
• Able to own data requirements and build efficient processes to support integration and data engineering with outlining data integration and validation requirements.
• Ready to experiment, pivot, and make data-driven decisions in a dynamic business environment.
• Proactively contribute ideas to the Product Backlog with ideas based on technical knowledge and capabilities.
• Be able to think outside of the box and find simple and elegant solutions to complex problems, including technical, product and processes-related ones.
• Curiosity and a drive to continuously learn within the domain.
• Have a truly entrepreneurial mindset.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

We are looking for a highly skilled Senior Data Scientist to join our team.  As a Senior Data Scientist, you will be responsible for designing and implementing advanced data models, analyzing complex business problems, and developing solutions that help optimize sales, marketing, pricing, and overall commercial performance in a leading American publishing house.

The role will contribute to the transition from primarily descriptive analytics toward more advanced, data-driven decision making.

Skills & Experience

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related field;
• 5+ years of experience in data science roles;
• Strong experience applying data science and machine learning to business problems, ideally in areas such as sales, marketing, customer behavior, demand forecasting, or pricing optimization;
• Proficient in Python and SQL for data analysis, scripting, and machine learning;
• Proficient in using agentic coding tools like Claude Code, Codex, Cursor
• Experience with SciKit-learn, Pytorch, and similar machine learning frameworks for building and deploying machine learning models;
• Experience working with modern data warehouses/lakehouses like Snowflake, Databricks, BigQuery, Redshift
• Strong analytical and problem-solving skills, with the ability to translate ambiguous business problems into data-driven solutions;
• Ability to work independently and collaborate with business and technical stakeholders;
• Fluent in English and excellent communication skills.

Nice to have: 

• Strong background in data science, with extensive experience in leveraging advanced analytics and machine learning to drive data-driven business decisions.

Responsibilities

• Design, develop, and implement advanced data models and machine learning algorithms to solve complex problems in the publishing domain, like author discovery;
• Analyze sales, marketing, customer, product, and pricing data to identify opportunities and support business decisions;
• Develop data-driven approaches to areas such as demand forecasting, customer behavior, sales optimization, marketing effectiveness, and pricing;
• Work with business stakeholders to understand broad or ambiguous business challenges and translate them into analytical and machine learning solutions;
• Collaborate with cross-functional teams to understand data requirements and deliver actionable insights and recommendations;
• Build and maintain scalable data pipelines using technologies such as Snowflake, and DBT;
• Leverage Python and SQL for data analysis, model development, experimentation, and automation;
• Utilize SciKit-learn, Pytorch and similar frameworks for developing and deploying machine learning models;
• Help evolve the organization from descriptive analytics toward predictive and prescriptive analytics and data-driven decision making;
• Stay current with emerging trends and technologies in data science and machine learning.

Workload: full-time, 100% remote
 Start: ASAP
 Duration: long-term
 Format: staff augmentation
 English: strong communication skills required
 

Project Overview
Fintech project. The client needs a strong Senior Data Scientist with hands-on LLM experience who can own the technical stack end to end, work with leadership on data science strategy, and explain technical decisions clearly to non-technical stakeholders.
 

What You’ll Do
Work with leadership to shape and implement the company’s data science strategy and find opportunities to use data for business value
Own the full technical stack needed for development and deployment
Develop and maintain scalable ML models and systems
Keep data management and engineering practices solid, with efficient data pipelines
Gather requirements from cross-functional teams and provide insights
Explain complex technical concepts to non-technical stakeholders
 

Must-Have Requirements
7+ years of total experience, including participating in and/or leading complex projects
Master’s or PhD in Data Science, Computer Science, Statistics or a related field, or equivalent knowledge and experience
Hands-on expertise in modern language models and ML frameworks
Practical experience with different LLMs of various sizes and from different providers
Optimizing LLM-based pipelines for performance and cost efficiency
Building agents that work across different tools and LLMs
LLM-based data capture and extraction
Experience with modern LLM-supporting frameworks and tools
Modern LLM prompting techniques
Building evaluation pipelines using data-driven approaches
Managing feedback and training pipelines, and fine-tuning models
Python, R, or another strongly typed language
Cloud platforms (AWS, GCP or Azure) and deployment processes
Excellent communication: must confidently explain ideas and technical decisions
 

Nice to Have
Big data technologies (Spark, Hadoop, data warehouse / data lake technologies)
Data architecture and database management background
Data management and engineering tools
Knowledge of accounting and bookkeeping
Commitment to ethical AI practices and data governance
 

Key Competencies
 Problem-solving and strategic thinking, ability to innovate and drive process improvements, collaboration.
 

CV must be reworked to match the requirements above