Jobs Data Science

We are looking for an experienced Senior Data Scientist to join our team and help unlock the full value of data across our platform, products, and business operations. In this role, you will apply advanced analytics, machine learning, and statistical modeling to generate actionable insights, improve decision-making, and drive innovation across the organization.

Responsibilities

• Analyze large, complex datasets to uncover trends, patterns, and insights that support strategic business and product decisions.
• Build predictive models to forecast business outcomes, improve operational efficiency, and support decision-making across multiple functions.
• Design and implement feature engineering techniques to improve machine learning model performance and accuracy.
• Partner with cross-functional teams including product, engineering, operations, and business stakeholders to identify opportunities and translate them into scalable data science solutions.
• Clean, preprocess, and structure data from multiple sources to ensure high-quality inputs for analysis and modeling.
• Develop, test, and deploy machine learning models for use cases such as classification, regression, clustering, recommendation systems, and forecasting.
• Evaluate and optimize model performance using appropriate statistical and machine learning metrics.
• Create dashboards, reports, and visualizations that clearly communicate findings and recommendations to technical and non-technical audiences.
• Automate recurring analysis, reporting, and model workflows to improve efficiency and consistency.
• Monitor production models and continuously improve performance, reliability, and business impact over time.
• Stay current with the latest advancements in data science, machine learning, and AI, and apply relevant innovations to PredictSpring’s platform and operations.

Requirements

• Excellent communication skills, including fluent verbal English, with the ability to explain complex concepts to non-technical stakeholders and collaborate effectively across teams.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist, with a strong background in machine learning, statistical analysis, and predictive modeling.
• Strong programming skills in Python preferred, or similar languages such as R, with hands-on experience using libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Expertise in building and deploying machine learning models for classification, regression, time-series forecasting, recommendation systems, and related applications.
• Strong experience with data wrangling, feature engineering, and working with structured and unstructured datasets.
• Proficiency in SQL for querying, transforming, and analyzing structured data.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for model deployment and data workflows.
• Experience with data visualization tools such as Power BI, Tableau, or Python visualization libraries.
• Strong analytical thinking, problem-solving ability, and a passion for applying data science to real-world business challenges.

Preferred Qualifications

• Familiarity with big data and distributed processing tools such as Apache Spark, Hadoop, or Databricks.
• Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Experience with natural language processing techniques such as text classification, sentiment analysis, or large language model applications.
• Strong foundation in statistical analysis, experimentation, and hypothesis testing.
• Experience collaborating with or supporting data engineering teams in building scalable data pipelines.
• Familiarity with version control tools such as Git.
• Strong business acumen and the ability to align technical solutions with business goals.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

Help us push AI further — and faster

LoopMe’s Data Science team builds production AI that powers real-time decisions for campaigns seen by hundreds of millions of people every day. We process billions of data points daily — and we don’t just re-apply old tricks. We design and deploy genuinely novel machine learning systems, from idea to prototype to production.

You’ll join a high-trust team that has a 5-star Glassdoor rating led by Leonard Newnham, where your work moves fast, ships to production, and makes measurable impact.

 What you’ll do:

• Design, build, and run large-scale ML pipelines that process terabytes of data
• Apply a mix of supervised learning, custom algorithms, and statistical modelling to real-world problems
• Ship production-grade Python code that’s clear, documented, and tested
• Work in small, agile squads (3–4 people) with DS, ML, and engineering peers
• Partner with product and engineering to take models from idea → production → impact
• Work with Google Cloud, Docker, Kafka, Spark, Airflow, ElasticSearch, ClickHouse and more

 What you bring:

• Bachelor’s degree in Computer Science, Maths, Engineering, Physics or similar (MSc/PhD a plus)
• 3+ years’ commercial Python experience
• Track record building ML pipelines that handle large-scale data
• Excellent communication skills — comfortable working across time zones
• A curious, scientific mindset — you ask “why?” and prove the answer

Bonus if you have:

• Experience with adtech or real-time bidding
• Agile / Scrum experience
• Knowledge of high-availability infrastructure (ElasticSearch, Kafka, ClickHouse)
• Airflow expertise

 About the Data Science Team:

We’re 17 ML engineers, data scientists, and data engineers, distributed across London, Poland, and Ukraine — acting as one team, not a satellite office.

What sets us apart:

• Led by an experienced Chief Data Scientist who codes, leads, and listens
• Inclusive, supportive culture where ideas are heard and people stay
• Strong values: open communication, continual innovation, fair treatment, and high standards
• Track record of publishing award-winning research in automated bidding

Don’t just take our word for it — check our Glassdoor reviews (search “Data Scientist”) for a real view of the culture.

 About LoopMe:

LoopMe was founded to close the loop on brand advertising. Our platform combines AI, mobile data, and attribution to deliver measurable brand outcomes — from purchase intent to foot traffic. Founded in 2012, we now have offices in New York, London, Chicago, LA, Dnipro, Singapore, Beijing, Dubai and more.

 What we offer:

• Competitive salary + bonus
• Billions of real-world data points to work with daily
• Flexible remote/hybrid options
• Learning budget and career growth support
• Friendly, transparent culture with strong leadership

 Hiring process:

1. Intro with Talent Partner
2. 30-min technical interview with Chief Data Scientist
3. Panel with 2 team members (technical, culture & collaboration)
4. Offer – usually within 48 hours of final round

 Are you ready to design and deploy AI systems that run at truly massive scale?

We are looking for a full-time Study-Level Biostatistician to support clinical trial projects in a CRO/FSP environment. The role is hands-on and focused on the development and review of study-level statistical documents, including Statistical Analysis Plans, statistical input to study documents, review of mock shells, and QC/review of Tables, Listings, and Figures.

The ideal candidate should have strong clinical trials biostatistics experience, excellent written and spoken English, and the ability to work independently with project teams, statistical programmers, and client stakeholders. Experience in ophthalmology and/or oncology therapeutic areas is strongly preferred.

Key Responsibilities

• Develop, review, and provide input into Statistical Analysis Plans.
• Provide statistical input into protocols, study-level documents, mock shells, and analysis specifications.
• Review Tables, Listings, and Figures for consistency with the protocol, SAP, mock shells, and statistical methodology.
• Perform statistical QC/review of outputs and provide clear comments to statistical programmers.
• Support definition of endpoints, analysis populations, visits/timepoints, subgroup analyses, and statistical methods.
• Work closely with statistical programmers to ensure correct implementation of planned analyses.
• Review and respond to client/sponsor comments related to statistical documents and outputs.
• Participate in study team meetings and communicate statistical topics clearly in English.
• Ensure study-level statistical deliverables are accurate, consistent, and compliant with applicable regulatory and project requirements.

Requirements

• Master’s degree in Biostatistics or Statistics is required.
• 3+ years of experience as a Biostatistician in clinical trials, preferably 5+ years.
• Hands-on experience developing and reviewing Statistical Analysis Plans.
• Strong experience with study-level statistical documents and clinical trial deliverables.
• Experience reviewing and performing QC of Tables, Listings, and Figures.
• Good understanding of clinical trial methodology, endpoints, analysis populations, and common statistical methods.
• Ability to work independently in a CRO, pharma, biotech, or FSP environment.
• Strong written and spoken English.
• Good communication skills and ability to interact with project teams and clients.
• Preferred therapeutic area experience: ophthalmology and/or oncology.
• Understanding of CDISC/ADaM and statistical programming deliverables is a plus, but programming is not the primary responsibility.

Nice to Have

• PhD in Biostatistics or Statistics.
• Ophthalmology and/or oncology experience.
• Experience in regulatory submissions.
• Experience working directly with sponsors/clients.

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics and banking.
 

The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast growing food delivery business. In this role, you will focus on time series forecasting, regression modeling, simulation modeling, and end-to-end machine learning pipelines to support resource planning and operational decision-making.

You will be responsible for developing simulation-based models that serve as a foundation for a digital twin of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity planning and operational optimization.

You will work closely with product, engineering, and operations teams to transform data into measurable business impact through production-ready ML and simulation solutions.
 

Job Responsibilities:

• Develop and implement time series forecasting models for resource planning (demand, capacity, couriers, delivery slots, operational load);
• Build regression and machine learning models to explain key drivers and support operational decisions;
• Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);
• Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in production using AWS SageMaker;
• Orchestrate training and inference workflows with Apache Airflow;
• Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable recommendations;
• Collaborate with product managers, engineers, and operations teams to define business problems and validate analytical solutions;
• Monitor model performance, forecast stability, and business impact over time.
   

Requirements:

• Bachelor’s Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics / Econometrics;
• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
• At least 2 years working experience on Data Science;
• Experience of the full cycle of model implementation (data collection, model training and evaluation, model deployment and monitoring);
• Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
   

Skills:

• Strong proficiency in Python with solid application of object-oriented programming (OOP) principles (modular design, reusable components, maintainable code);
• Solid experience in time series forecasting and regression modeling;
• Practical knowledge of:o Classical and ML forecasting techniques;
  o Statistical methods (hypothesis testing, confidence intervals, A/B testing);
• Advanced SQL skills (window functions, complex queries);
• Experience building automated ML pipelines;
• Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
   

Nice to have:

• Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);
• Experience with Apache Airflow for data and ML workflow orchestration;
• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);
• Experience working with large-scale production data systems.
   

What We Offer:

• Competitive salary;
• Professional & personal development opportunities;
• Being part of dynamic team of young & ambitious professionals;
• Corporate discounts for sport clubs and language courses;
• Medical insurance package.

About the Company

We are a specialized consulting company focused on Statistics, Data Science, and AI. We work across multiple industries, including the public sector, insurance, and other data-intensive domains.

For this role, we are specifically looking for a Senior Data Engineer to join projects in the public sector. These projects involve building technically advanced solutions that also create a meaningful positive impact on society.

What You'll Be Doing

• Co-design, manage, and lead consulting projects in Data Science and AI
• Independently advise stakeholders on the client side
• Perform data management, data preparation, analysis, and interpretation
• Prepare and present results, and derive actionable recommendations
• Provide technical leadership and mentor team members
• Contribute to business growth through client acquisition and sales activities
• Identify new business opportunities and maintain existing client relationships
• Represent the company externally
• Contribute to the strategic development of the company

Requirements

• Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Business Administration, or a related quantitative field
• At least 5 years of experience in Data Science, AI, Advanced Analytics, or Consulting
• Strong expertise in at least one core area, with solid knowledge across related domains
• Experience working with databases and large-scale (Big Data) systems
• Strong programming skills in Python and R
• Excellent communication and consulting skills
• Experience interacting with stakeholders across different departments and seniority levels
• Leadership experience (ideally managing teams of 3–8 people)
• Proven project management and project leadership experience
• Strong sense of responsibility, teamwork, and problem-solving mindset
• Fast learner, adaptable, and easy to work with
• English — B2
• Ukrainian — Native
• Regular business trips within Germany are required

What We Offer

• Dynamic environment with flat hierarchies and high ownership
• Flexible working hours and remote work options
• Individual learning and development opportunities
• Diverse and interdisciplinary team

We are looking for a Data Scientist to join a risk modeling team within one of the leading banks in Ukraine. The team has been a benchmark in risk modeling for over 10 years, applying advanced Machine Learning techniques and global best practices.

We are open to considering candidates from Junior to Senior level, depending on experience and expertise.

In this role, you will develop ML solutions to minimize financial risks and optimize strategies for working with millions of customers.

Why Join the Team:

• Technology Stack: We use cloud solutions and modern development tools such as Amazon SageMaker, Amazon S3, Git, Confluence, etc.
• Scale: Working with large-scale datasets to support critical business decisions.
• Expertise: Risk models aligned with international standards and regulatory requirements.
• Professional Community: Strong Data Science community, regular internal workshops, participation in conferences, and sponsored learning.
• Automation: Proprietary system for managing the full ML lifecycle (from development to monitoring).

Key Requirements:

• 2+ year of experience in Data Science (experience in FinTech/Banking will be a strong advantage);
• Strong proficiency in Python for data analysis (NumPy, Pandas, SciPy, etc.) and experience optimizing SQL queries on large datasets;
• Hands-on experience with ML frameworks such as Scikit-learn and gradient boosting libraries (LightGBM, XGBoost, etc.);
• Experience with time series analysis and forecasting tools (Statsmodels, Prophet, etc.);
• Solid understanding of mathematics behind models (from linear regression to gradient boosting) and model evaluation techniques;
• Understanding of Big Data concepts and experience with version control tools (Git).

Nice to Have:

• Experience with Docker and/or MLflow;
• Knowledge of financial regulations (e.g., Basel III, IFRS 9).

Key Responsibilities:

• Credit Risk Modeling: Develop portfolio risk models (PD, LGD, EAD) in line with IFRS 9 requirements;
• Income & Solvency Forecasting: Build ML models to assess customer financial condition based on transactional activity;
• Credit & Behavioral Scoring: Develop classical and advanced scoring systems for automated decision-making across the customer credit lifecycle;
• Market Risk Analysis: Apply time series analysis and ML techniques to assess liquidity risk, forecast FX volatility, and model customer fund behavior;
• Fraud & Anomaly Detection: Build and maintain systems for detecting unusual transaction patterns in real time;
• ML Lifecycle: Participate in the full lifecycle of models — from idea and data collection to automated monitoring and retraining.

What We Offer:

• Opportunity to work in one of the leading banks in Ukraine;
• Official employment and 24+4 calendar days of vacation;
• Sick leave compensation;
• Competitive salary;
• Bonuses and performance-based incentives;
• Medical insurance;
• Corporate training and development programs;
• Remote work options;
• Financial support in critical situations.

Remote – Full-time – Flexible Hours - Shifted schedule to EST (New York) timezone

About TenViz

TenViz Predictive Analytics builds AI-powered solutions that help Fortune 100 investors anticipate market shifts before they become consensus. We combine financial expertise, mathematical rigor, and AI research to deliver predictive analytics for institutional investors.

Your Expertise

• Strong interest in quantitative and algorithmic approaches
• BSc/MSc in Math, Physics or related field with solid background in statistics, linear algebra and probability theory
• Advanced Linear Algebra, Advanced Statistics, Using Linear Algebra methods in Statistical analysis
• 2+ years in data research, quantitative modeling, ML prototyping, and backtesting
• Skilled in Python, SQL, Git
• Experience with  experiment tracking, pipeline orchestration and workflow automation

Nice to have:

• Bayesian inference, reinforcement learning, or ensemble methods
• Financial econometrics, time-series forecasting, or regime modeling

What You’ll Do

• Design predictive models using probabilistic, ML, and hybrid approaches
• Analyze large-scale financial datasets to detect hidden patterns and early regime shifts
• Prototype and evaluate algorithms, from deep learning to Bayesian models
• Write production-grade research code in Python/SQL that integrates into pipelines
• Translate results into insights and themes investors can act on — not just outputs

Example projects:

• Forecasting inflation via commodity price signals
• Constructing probabilistic forecasts of currency moves around macroeconomic announcements
• Designing a Bayesian model to estimate recession probabilities from yield curve dynamics
• Designing a regime-aware ML pipeline that switches models depending on market conditions
• Creating hybrid ensembles that outperform traditional benchmarks

What’s in It for You

• Remote-first, flexible hours
• Paid vacation & holidays (after 8 months)
• Continuous learning: advanced ML/DL workshops, probabilistic methods, optimization
• Supportive, collaborative team — no micromanagement, focus on trust and creativity
• Work on real financial problems where your models influence billion-dollar decisions

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We’re currently looking for a Data Engineer/Analyst (GCP) to join our team. In this role, you’ll design, implement, and deliver robust data platforms and analytics solutions on Google Cloud - ensuring technical excellence and client success across the full project lifecycle, from pre-sales discovery to enterprise delivery and internal projects. We’re excited to meet someone who’s ready to make a real impact.

Requirements

- Fluency in Ukrainian
- At least B2 level in English
- GCP Native Data Stack: Deep practical knowledge of BigQuery, Cloud Storage, Cloud Functions, and BigQuery ML.
- 3+ years of experience in Data Engineering
- Strong experience with Dataflow, Dataproc, Pub/Sub, Cloud Composer, or Dataform for building and maintaining optimized ETL/ELT processes in GCP.
- Proficiency in Looker / Looker Studio.
- Advanced SQL (focus on optimization and performance tuning) and Python (for API integrations and pipeline scripting).
- Comfortable in client-facing and pre-sales scenarios (live demos, requirements gathering) with the ability to translate business needs into scalable technical designs.
- A proactive, self-driven approach with high responsibility for data platform reliability and accuracy.
- Familiarity with integrating data from APIs, relational databases, NoSQL systems, and SaaS platforms.
- Ability to work seamlessly with architects, DevOps, and ML engineers to deliver end-to-end cloud solutions.

Responsibilities

- Design and build modern data platforms for enterprise clients, working with both structured and unstructured datasets at scale.
- Lead the implementation of analytics solutions ensuring strict data quality, security, and rigorous performance optimization.
- Run workshops and deliver technical presentations to stakeholders to define and refine data architectures.
- Continuously monitor and tune BigQuery cost/scalability models and ETL performance.
- Collaborate with the team during discovery phases to provide technical expertise, live demos, and solution scoping.
- Identify and explore new GCP features and agentic AI tools to automate operations and improve process analytics.

Work conditions

- Flexible Work Format: Work remotely with flexible hours, allowing you to balance your professional and personal life efficiently.
- Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
- International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
- Expand your expertise by engaging with international markets across the EMEA and CEE regions.
- Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.

When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

Skills requirements:
• Strong Python Experience (1 year +);
• Experience with LLM , Diffusion models (1 year +);
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

Key responsibilities:
• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

QIT Software is looking for a Data Scientist for Luxury Real Estate Website. ( PART TIME)


Requirements:

- Strong experience in data analysis, research, or journalism — ideally within real estate, property, or luxury consumer markets
- Strong source-evaluation instincts: you can tell a credible, citable figure from an unverified claim and know when a second source is required
- Proficiency working inside CMS platforms (WordPress experience a plus) and comfort with AI-assisted content tools
- Excellent written English — able to turn raw data into clean, concise market commentary for a professional readership
- High attention to detail: you catch a figure that's been rounded differently across two sources, and you follow it up
- Self-directed and organised — capable of managing a rolling workload without close supervision, meeting regular weekly and quarterly deadlines
- Familiarity with the branded residences sector, luxury hospitality, or international property markets is a strong advantage
- Experience working with structured data from multiple formats (PDFs, web articles, press releases) preferred

Responsibilities:

- Review and audit existing market pages to ensure every data point is accurate, current, and properly sourced
- Cross-reference figures against primary sources — market reports, press releases, and news articles — flagging any that lack credible attribution
- Update market data using the internal AI builder and WordPress CMS on a rolling basis as new information becomes available
- Monitor inbound press releases and scraped news content, extracting relevant market figures and tagging them for ingestion
- Produce weekly market insight summaries highlighting notable data changes, emerging trends, and pipeline activity in the branded residences sector
- Compile quarterly reports synthesising market performance across key geographies, brands, and project types
- Maintain a source log that documents the origin, date, and confidence level of every figure on the platform
- Proactively identify gaps in coverage and surface recommendations for new data categories or geographies to track

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world. 

Our client is an innovative technology company developing advanced AI-powered solutions for enterprise and industrial environments. The organization focuses on leveraging artificial intelligence to optimize complex engineering, manufacturing, and supply chain processes through intelligent software platforms and data-driven decision-making.

The role supports two strategic AI initiatives aimed at transforming engineering and supply chain operations. The first program focuses on accelerating systems engineering lifecycles through NLP, Large Language Models, and automated compliance checking of complex technical and regulatory documentation. The second program is dedicated to predictive supply chain intelligence, including demand forecasting, spend analytics, supplier risk assessment, and anomaly detection. The technical environment includes enterprise ERP systems, engineering data models, Data Lakehouse infrastructure, and large-scale AI platforms integrated through RESTful services.

Responsibilities

• Design, develop, and deploy production-grade machine learning and AI solutions.
• Fine-tune and optimize Large Language Models (LLMs) for domain-specific use cases involving technical and regulatory documentation.
• Build NLP pipelines capable of extracting structured rules and business logic from unstructured text sources.
• Design and implement Retrieval-Augmented Generation (RAG) architectures for intelligent querying of large technical knowledge bases.
• Develop time-series forecasting models for spend prediction, demand planning, and supply chain optimization.
• Build machine learning models for supplier risk scoring, anomaly detection, and operational analytics.
• Create scalable data extraction, transformation, and feature engineering pipelines from structured and unstructured data sources.
• Collaborate with Data Engineers and Backend Engineers to integrate AI models into enterprise applications through RESTful APIs.
• Optimize model performance, scalability, and reliability for large-scale processing workloads.
• Validate model outputs, analyze model performance, and continuously improve prediction quality and accuracy.
• Work closely with Product Managers, Domain Experts, and Engineering teams to ensure business requirements are translated into effective AI solutions.

Requirements

• 5+ years of commercial experience in Data Science, Machine Learning, or Artificial Intelligence.
• Strong programming skills in Python.
• Hands-on experience with Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.
• Strong experience with Natural Language Processing and transformer-based architectures such as GPT, BERT, Llama, or similar models.
• Experience with prompt engineering, fine-tuning, and implementation of Large Language Models.
• Proven experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
• Experience building and deploying machine learning models into production environments.
• Strong understanding of supervised and unsupervised machine learning techniques.
• Experience developing forecasting, classification, and predictive analytics models.
• Solid knowledge of statistics, probability theory, experimentation, and model evaluation methodologies.
• Experience working with SQL and/or NoSQL databases.
• Familiarity with complex data formats such as JSON and XML.
• Understanding of REST APIs and backend integration using frameworks such as Flask or FastAPI.
• Ability to quickly understand complex domain-specific terminology and translate business requirements into scalable AI solutions.
• Experience working within Agile or Sprint-based delivery environments.
• Strong analytical thinking, problem-solving, and communication skills.
• Upper-Intermediate or higher English level.

Nice to Have

• Experience with SAP S/4HANA or other ERP platforms.
• Experience working with Data Lakehouse architectures and large-scale enterprise data environments.
• Familiarity with specialized engineering data models or other specialized data structures.
• Experience with graph databases or graph-based data modeling.
• Knowledge of compliance automation, regulatory interpretation, or document intelligence solutions.
• Experience in manufacturing, industrial, supply chain, engineering, or other highly regulated industries.
• Exposure to MLOps practices and cloud-based AI/ML platforms.

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 the first Data Science engineers to join our team and play a foundational role in building a private Large Language Model from the ground up. This is a rare opportunity to shape the technical direction, influence architectural decisions, and establish best practices for intelligent systems within the organization.

What you will do: 

• Design, build, and maintain classical machine learning models to support core product needs.
• Develop agent-based systems (LLM agents, multi-step agents, agent-to-agent workflows) as part of the broader LLM ecosystem.
• Conduct rigorous experiments and iterate quickly to validate approaches and improve system performance.
• Build and optimize inference pipelines, including performance tuning, monitoring, and alerting.
• Collaborate closely with Data Engineering to deploy models securely and reliably into production environments.

• Contribute to defining standards, workflows, and tooling for the new Data Science function.

   

What we expect:

• 3+ years of hands-on experience with Python.
• Strong SQL skills and understanding of data workflows.
• Solid grasp of machine learning methods and their practical applications.
• Experience building agents or agent-based systems is a strong plus.
• Initiative, ownership, and readiness to work in a greenfield environment where many solutions must be defined from scratch.

Role Overview

We are a systematic prop trading firm operating at the intersection of CeFi and DeFi, with infrastructure deployed across 50+ exchanges and 20+ chains.
 

We are looking for a Senior Quantitative Researcher & Algorithmic Strategist to join the trading team. In this role, you will fully own the lifecycle of trading strategies — from research and backtesting to production deployment and optimisation.
 

This is a high-autonomy, high-impact position with direct collaboration with the founding team.
 

Key ResponsibilitiesStrategy Development

• Develop proprietary alpha signals or adapt existing strategies
• Design, backtest, and forward-test systematic trading strategies
• Conduct statistical validation (walk-forward, out-of-sample, regime analysis)
• Analyse capacity, decay, and correlation within the portfolio
• Prepare research documentation and performance reports
   

Engineering & Deployment

• Translate research into production-grade code (Python / C++ / Rust)
• Build algorithms for CEX market-making programs (Binance, OKX, Bybit)
• Improve order book logic (spread, inventory, execution efficiency)
• Integrate strategies into low-latency infrastructure
• Monitor live performance and conduct post-trade analysis
   

Market Microstructure & Execution

• Optimize fill rates, slippage, and latency
• Work with order book dynamics and execution logic
• Improve rebate capture and maker program performance
   

RequirementsHard Requirements (Must-have)

• Proven live trading track record (real P&L, not only backtests)
• Strong knowledge of crypto market microstructure
• Production-level coding in Python
• Working knowledge of C++ or Rust (preferred)
• Strong quantitative background (statistics, probability, time-series)
• Experience with exchange APIs (REST/WebSocket)
• Ability to own strategies end-to-end independently
   

Nice to Have

• Experience in prop trading / HFT / crypto quant firms
• Market-making algorithm experience
• Experience with CEX maker programs
• Familiarity with DEX / on-chain trading / MEV
• Experience in arbitrage strategies (CeFi–DeFi / cross-venue)
• Risk management systems (PnL limits, volatility sizing)
   

Academic Background

• Degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar
• Practical track record is prioritized over formal education
   

What We’re Looking For

• Strong ownership mindset over strategies and results
• Ability to explain and defend your edge
• Deep understanding of why strategies work (and fail)
• Attention to execution details (fees, latency, fills)
• Intellectual honesty and data-driven thinking
• Collaborative, non-ego-driven approach
   

Compensation

• Base Salary: Competitive (USD / stablecoin)
• Performance Bonus: P&L-based allocation (high-water mark model)
• Capital Allocation: Up to $100M+ per strategy (based on performance)
• Infrastructure: Full access to trading stack (50+ venues, low latency)
• Format: Remote-first, high autonomy
   

What We Offer

• Ready-to-use trading infrastructure (no need to build from scratch)
• Direct access to decision-makers
• Fast capital deployment
• Exposure to cutting-edge crypto markets (CEX + DEX)
• Collaborative research environment
• Flat team structure
   

Hiring Process

1. Call with Recruiter (30 min) — background and strategy discussion
2. Team interview (60 min) — strategy walkthrough
3. Final C-level Interview (30 min) 

About AIstats

AIstats is transforming the football data market by moving from 2D to 3D, powered by a cutting-edge Computer Vision and Machine Learning ecosystem that unlocks deep insights for both fans and professionals.

What we build

Advanced Football Analytics — a mobile app for football fans an— a mobile app for football fans and bettors that reached 100k MAU in less than a year, featuring advanced statistics powered by our proprietary ML and Computer Vision technologies.

Advanced Analytics for Football Clubs — a next-generation analytics platform helping football clubs, scouts, and agents make smarter decisions both on the pitch and in the transfer market. Thanks to our early leadership in skeletal tracking data, AIstats secured several Tier-1 club partnerships within months of launching the platform.

Responsibilities

• Develop and improve statistical and machine learning models
• Analyze large-scale datasets using Python and SQL
• Conduct statistical analysis, hypothesis testing, and experiment evaluation
• Build interpretable ML solutions and explain model behavior
• Collaborate with cross-functional teams on data-driven initiatives

Requirements

• 3+ years of experience as a Data Scientist
• Strong Python skills with NumPy, Pandas, and scikit-learn
• Solid SQL knowledge; R is a plus
• Strong understanding of probability theory and mathematical statistics
• Experience with statistical testing: t-test, χ², ANOVA, Mann-Whitney, Wilcoxon, KS test, bootstrap/permutation tests, Bonferroni and FDR corrections
• Hands-on experience with XGBoost, LightGBM, and CatBoost
• Understanding of Bayesian methods
• Experience with longitudinal/panel data, mixed/fixed/random effects models, and repeated measures
• Experience with interpretable ML approaches: GAM, SHAP, partial dependence, counterfactual analysis

Nice to Have

• Experience with deep learning: Transformers, attention mechanisms, RNN/LSTM
• Knowledge of Graph Neural Networks
• Experience with Reinforcement Learning: PPO, MAPPO, MAT, multi-agent RL
• Familiarity with Google Research Football or similar environments
• Advanced Bayesian statistics: PyMC, Stan, numpyro, MCMC, hierarchical models
• Experience with causal inference: DAGs, instrumental variables, difference-in-differences
• Knowledge of probabilistic spatial models: Markov chains, HMM/DBN, MRF/CRF, Gaussian processes

What we offer

• Fully remote work format;
• Flexible start of the working day and convenient schedule;
• Stable competitive salary pegged to the USD;
• 24 days of paid vacation and 15 additional paid days off (including sick leave, corporate holidays, and national/religious holidays);
• Friendly communication culture, great product, and transparent processes;
• Dynamic work environment with a passionate team that loves sports and technology;
• Opportunities for professional growth and career development;
• No micromanagement — just trust, autonomy, and freedom to experiment.

Join our team and help drive innovation in the football industry!

Equals5 helps pharmaceutical companies run precisely targeted ad campaigns on social platforms by identifying healthcare professionals and the consumer signals that reach them. The Identity team builds the data, scoring, and targeting systems that make this possible.

We are looking for a Data Analyst  to join the Identity team at Equals5. This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place. Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.

Dashboards and visualizations are part of how findings get communicated, but they come at the end — the surface of the work, not its core. Most of your time is spent on what sits underneath: methodology, judgment calls on data quality, and shaping how the domain understands its own numbers.

Responsibilities

• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.

Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus 

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.

Nice to have

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

What We Offer

• Fully remote with flexible hours, with working overlap in CET ±2 hours for syncs.
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech — both for daily work and as part of product logic.
• High-Impact Role: You will directly shape how we identify, score, and reach healthcare professionals — the core business of our domain.
• Small team, direct impact: You will work directly with Product and Engineering leads — no layers between you and the people making decisions.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.