Jobs Data Science

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

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.

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide
 

About your role: In this role, you will directly influence product growth and monetization by improving Recommendation Systems for gifts and coins. You’ll work end-to-end on ML solutions — from defining the Data Science roadmap and running experiments to deploying production-ready models — while collaborating closely with Product Managers, Analysts, and Engineers. The role offers a combination of hands-on machine learning, recommendation systems, MLOps, and strategic ownership in a fast-paced product environment where your work will have visible business impact.

In this role, you will

• Create, develop, and improve machine learning models to enhance business performance and product effectiveness
• Collaborate closely with cross-functional teams, including Product Managers, Analysts, and Engineers, to deliver innovative ML-driven features and improvements
• Apply expertise in machine learning algorithms, data structures, and optimization techniques to improve model accuracy, scalability, and efficiency
• Implement and maintain MLOps best practices for model deployment, monitoring, retraining, and maintenance in production environments
• Investigate, troubleshoot, and resolve technical issues related to machine learning models, data pipelines, and infrastructure
• Stay up to date with the latest advancements, technologies, and best practices in machine learning, artificial intelligence, and data science

It’s all about you

• 4+ of Machine learning and deep learning on tabular data, Recommendation systems. 
• 4+ years of software development experience in Python with experience working with ML and DL
• Experience in designing a data science roadmap and the leading technical execution of the project
• Experience with Cloud development AWS/GCP
• Experience of deploy API models on Dev/Prod environment
• Practical understanding of A/B tests process
• Practical understanding of the mathematics behind modern machine learning, linear algebra, and statistics.
• Extensive SQL knowledge

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Maternity recovery support allowance 
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process

• Intro call
• Technical Interview
• Final Interview
• Reference check
• Offer

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.

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

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.

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) 

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

Duration: 3-6 months

Must Have Skills:

• Senior-level Data Science / ML ownership — 5+ years
• ETL / data pipelines for ML — 3+ years
• Python + production ML / MVP delivery — 4+ years
• Geospatial / positional / logistics-related data - any exp

About the Project
We are looking for a Senior Data Scientist / ML Engineer to support a Berlin-based logistics technology product company on a data science project focused on building a production-ready MVP.
The project is currently in an early research / proof-of-concept stage. Initial validation has shown that the concept is technically feasible, and the next step is to bring it from research into a usable MVP that can be integrated into the existing product infrastructure.
The solution will use positional / location-based data to identify specific locations and generate insights that help drivers and improve operational efficiency.
This is not a fully isolated greenfield project. The work will be connected to existing internal systems, data pipelines, and infrastructure. Therefore, the ideal candidate should be highly autonomous, senior enough to clarify requirements directly with internal stakeholders, and able to take ownership of the solution with limited day-to-day supervision.

Responsibilities

• Own the data science and ML development work from research validation to a usable MVP.
• Build and improve data pipelines and ETL processes that feed the model.
• Work with positional / geospatial / location-based data.
• Develop, validate, and iterate on ML models that identify relevant locations and generate useful outputs for the product.
• Prepare the model and pipelines to run in production on a scheduled basis.
• Work with internal data, product, and engineering teams to understand available data, infrastructure, constraints, and business requirements.
• Translate high-level product and business goals into technical implementation steps.
• Make technical decisions independently while keeping internal stakeholders aligned.
• Document the solution, assumptions, limitations, and handover materials for the internal team.
• Ensure that the MVP can be further scaled, improved, and integrated into the company’s existing product suite.

Required Experience

• 5+ years of experience in Data Science, Machine Learning, or ML Engineering.
• Strong hands-on experience building ML models from concept to production or MVP stage.
• Experience working with ETL processes, data pipelines, data preparation, and model input pipelines.
• Strong Python experience and common data science / ML libraries.
• Experience working with large datasets and imperfect real-world data.
• Ability to work with positional, geospatial, mobility, logistics, or location-based data.
• Experience deploying or preparing ML models for production usage.
• Strong understanding of model evaluation, iteration, and practical trade-offs between accuracy, speed, and business value.
• Ability to work independently with limited day-to-day guidance.
• Strong ownership mindset: ability to clarify requirements, identify blockers, communicate with stakeholders, and drive the work forward.

Nice to Have

• Experience in logistics, transportation, mobility, route optimization, delivery, or fleet-related products.
• Experience with cloud data infrastructure such as AWS, GCP, or similar.
• Experience with scheduled production pipelines, batch processing, or workflow orchestration tools.
• Experience handing over ML solutions to internal engineering or data teams.
• Previous experience in startup or product-company environments.

We are looking for a Senior Data Scientist to help build data-driven products that significantly improve customer experience on a large-scale betting platform. You will work on high-impact machine learning models, take full ownership from research to production, and directly influence product and business decisions. This role goes beyond modeling – you will deploy models into production, run experiments, monitor results, and partner closely with product and business teams.

You will work on models and systems such as:

• Churn, retention and LTV prediction;
• Risk scoring, fraud and responsible gambling models;
• Personalization and recommendation systems;
• Uplift and causal models to drive product decision;
• Real-time ML systems powering user experience;

• Experimentation frameworks and A/B testing.

   

What you’ll be doing:

• Design, train and productionize machine learning models for product, risk and personalization use cases;
• Own models end-to-end: data exploration, feature engineering, modeling, deployment and monitoring;
• Design and analyze A/B tests to measure the real business impact of models and product changes;
• Collaborate closely with product managers, engineers and analysts to translate business problems into ML solutions;
•  Monitor model performance, data quality, drift and key business metrics after deployment;

• Communicate insights and recommendations to business and product stakeholders.

   

What we’re looking for:

• 4+ years of experience as a Data Scientist or in a similar applied ML role;
• Strong hands-on experience with Python and SQL;
• Proven experience building and deploying ML models in production;
• Experience with churn, LTV, behavioral or risk-related models;
• Solid understanding of statistics, experimentation and A/B testing;
• Ability to clearly explain technical results to non-technical stakeholders.

Nice to have:

• Experience in gaming, fintech or other high-scale consumer products;
• Experience with recommendation systems or risk/fraud models;
• Familiarity with cloud environments and basic MLOps practices;
• Experience working with real-time or near real-time ML systems.

Who We Are:

We are DATA.BET, a product IT company that develops comprehensive technological solutions for sports, esports, and virtual sports betting in a single sportsbook.
Our key products - Odds Feed, AI-powered risk management system, and fast Single Page Application - help partners gain stable profits and a competitive advantage.
Our team consists of more than 250 professionals. 

Join us in developing a data science and ML offering for a comprehensive workforce management platform serving enterprises across industries and regions. We are looking for a Senior Data Scientist to own the direction and delivery of the Intelligence Pack. This analytical and ML layer turns platform data into predictive value for customers.

This is the first dedicated data science hire on the project. You will set standards, shape the roadmap in partnership with the Product team, and deliver much of the work yourself – across the full analytics lifecycle: from data architecture and predictive insights to customer-facing dashboards. The role requires a strong combination of technical depth, product mindset, and the ability to work autonomously across multiple stakeholders.
Enterprise SaaS platform for workforce management and talent acquisition.

Requirements

• Strong applied data science skills: building predictive models, surfacing patterns, and shipping ML/AI features into production
• Excellent SQL and data modelling skills; ability to design, refactor, and optimise warehouse structures
• Proven experience delivering customer-facing dashboards (Metabase or similar) where accuracy and performance both matter
• Hands-on experience with query optimisation, version control, and structured analytics development practices
• Product-minded approach: ability to think about users, value, and trade-offs as naturally as about schemas
• Experience helping define the product direction or roadmap for a data product, intelligence layer, or analytics offering
• Credibility to set standards and lead through influence as a senior individual contributor
• Strong communicator across product, engineering, commercial, operations, and customer audiences
• Comfortable engaging directly with customers on reporting and insights
• Upper-Intermediate English level or higher

Would Be a Plus

• Experience introducing tooling and processes that speed up analytics development while improving quality and consistency
• Experience working across analytics engineering, business intelligence, and data science disciplines within a single role
• Experience supporting customer-facing analytics, reporting, or intelligence products
• Interest in growing a data capability and taking on broader leadership responsibilities as the function scales

Responsibilities

• Own the long-term direction of the Intelligence offering, spanning data models, analytics, and customer-facing insights
• Partner with the Product team to build and evolve the data science roadmap
• Design and evolve the data architecture and canonical data model underpinning Intelligence
• Develop and ship data science work: predictive signals, pattern detection, and automated insights
• Design and deliver dashboards that customers trust and rely on
• Own analytics engineering end-to-end: modelling data, optimising queries, versioning work, and reviewing changes before they reach customers
• Establish architectural principles, analytical standards, and ways of working that allow Intelligence to scale
• Work closely with Engineering to ship Intelligence features into the product
• Engage directly with customers to understand reporting needs, explain insights, and validate value
• Support Commercial and Operations teams with insights that underpin upsell, renewal, and decision-making
• Provide insights and what-if analysis tooling for C-Suite customers

BETER is a rapidly growing product company. We create competitive content supplemented with analytics. For more than 5 years, we have been organizing sports tournaments, broadcasts, and developing our own sports community. We hold 45,000+ events per month in esports and traditional sports, and our products are represented in 150+ countries worldwide.

We are looking for a hands-on Data Science Tech Lead to join our team and drive the development of sports analytics and prediction products. This role combines deep technical expertise in machine learning and mathematical modeling with team orchestration and delivery ownership.

You will work closely with the Engineering Manager and lead a team of 4 Data Science Engineers, helping transform business needs and production challenges into scalable data science solutions.

Responsibilities:

• Collaborate with the Engineering Manager to coordinate and support a team of 4 Data Science Engineers
• Collect and analyze business requirements, production issues, and product needs, transforming them into actionable data science tasks and backlog
• Analyze large volumes of sports, esports, and trading data
• Develop and improve sports prediction models using statistics and machine learning techniques
• Conduct, automate, and evaluate data-driven experiments
• Integrate mathematical and ML models into production workflows
• Participate in hands-on development and coding activities
• Perform code reviews and maintain high engineering and data science quality standards
• Ensure efficient execution and delivery of data science initiatives within the team

Requirements:

• Previous experience in a Tech Lead or team leadership role
• Strong hands-on programming skills in Python
• Advanced knowledge of databases and data processing
• Strong expertise in machine learning, statistics, and probability theory
• Experience building and deploying mathematical or predictive models
• Upper-Intermediate+ level of English
• Ability to balance technical leadership with hands-on engineering work

What we’re looking for:

This is primarily a hands-on engineering role. The main focus is building mathematical models, writing production-level code, and delivering real business impact through data science solutions.

At the same time, the role requires strong coordination skills — the ability to distribute work effectively within the team, support engineers, and ensure successful delivery together with the Engineering Manager.

Successful probation expectations:

During the probation period, we expect the successful delivery of a sports analytics or modeling product through:

• effective team orchestration,
• hands-on contribution to development,
• and high-quality execution of data science workflows.

Ideal candidate profile:

We would love to meet someone who is:

• proactive in communication and information gathering,
• focused on data-driven decision making,
• detail-oriented and demanding when it comes to production quality and best practices.

Also relevant:

• High-load real-time data environments, such as fintech, gaming, marketing analytics, computer vision, or similar domains, working with large-scale data streams.

We offer:

• Ability to work remotely
• Competitive and timely payment for services
• Flexible work schedule
• Personal mentoring and coaching
• Team building and corporate events
• 100% paid sick leave
• 20 working days of paid vacation
• Paid child care leave

Middle Software Engineer (Computer Science Educator – Innovative STEM School, Spain)

Location: Southern Spain
Job Type: Full-time
Start Date: September 2026

🚀 About the Role

We are looking for a passionate Middle-level Software Engineer who is excited not only about building technology, but also about shaping the next generation of innovators.

Join a forward-thinking international STEM school where Computer Science is taught as a tool to understand and transform the world. This is a unique opportunity to combine your engineering expertise with mentoring, problem-solving, and real-world application of technology.

💡 What You’ll Do

• Design and deliver engaging Computer Science learning experiences based on real-world challenges
• Mentor students in programming, algorithms, and software development practices
• Contribute to building a modern, innovation-driven curriculum
• Inspire problem-solving, critical thinking, and creativity
• Support students in projects, competitions, and research initiatives
• Collaborate with an international team of educators and tech enthusiasts

🧠 What We’re Looking For

• 2–5 years of experience in software development (any modern stack)
• Strong understanding of Computer Science fundamentals (algorithms, data structures, systems thinking)
• Passion for sharing knowledge and mentoring others
• Experience with project-based or collaborative environments
• Strong communication skills in English
• Interest in education, innovation, or EdTech is a big plus

🌍 Why This Role is Different

• Work in a startup-like educational environment with freedom to innovate
• Combine software engineering + impact-driven work
• Live and work in Southern Spain 🌞
• Be part of building a next-generation learning model
• Opportunity to grow into leadership, curriculum design, or tech-education hybrid roles

🎯 Ideal Candidate

You’re a developer who:

• Enjoys solving real-world problems
• Wants to go beyond routine coding
• Is curious, creative, and impact-driven
• Would love to inspire others while continuing to grow technically

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?