Jobs Data Scientist

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.

We are looking for a Senior Data Scientist to lead the design and implementation of next-generation AI solutions for Lifecycle Marketing.

As a senior member of our team, you will shape methodology, guide product direction under uncertainty, and represent us in high-stakes conversations with customers. You’ll combine deep expertise in causal inference, reinforcement learning, and experimentation with strong communication skills to drive impact across the company and with our clients.


Responsibilities:
 

• Own the design and methodology of data science solutions for lifecycle marketing, with emphasis on causal inference, uplift modeling, and reinforcement learning.
• Lead the development of experimentation frameworks (A/B/n tests, variance reduction, policy evaluation).
• Research, prototype, and productionize multi-armed bandits and contextual RL approaches for personalization and timing optimization.
• Take a strong, opinionated role in brainstorming sessions, guiding decision-making in areas of high uncertainty.
• Represent us in front of customers, translating complex modeling decisions into clear business value.
• Mentor junior and mid-level team members, raising the technical bar across the team.
• Collaborate closely with product managers, engineers, and analysts to align data science strategy with business goals.
  
   

Requirements:
 

• M.Sc. or Ph.D. in Computer Science, Statistics, Mathematics, or related field.
• 6+ years of hands-on data science experience, including direct work with lifecycle marketing, personalization, or customer analytics.
• Advanced expertise in statistics, causal inference, and experimental design.
• Proven track record of implementing reinforcement learning / multi-armed bandit models in production.
• Strong software engineering skills in Python, SQL, and ML frameworks
• Exceptional communication skills — able to influence internal teams and present to executive-level customers.
• Entrepreneurial mindset: thrives in uncertainty, challenges assumptions, and pushes for impactful solutions.

About the Role
We’re looking for a GenAI Engineer to design and build production-grade AI capabilities, including intelligent agents, LLM-powered features, and workflow automation. In this role, you’ll collaborate closely with product, engineering, and design teams to integrate cutting-edge AI technologies into customer-facing products at scale.

You’ll join a US-based team developing one of the world’s leading enterprise video platforms, used for live streaming, virtual events, online training, and webinars by thousands of users worldwide.

Requirements:

• Strong software engineering background (Python preferred)
• Proven track record of building production-grade GenAI applications
• Hands-on experience with LLMs, RAG, AI agents, vector databases, and AI orchestration frameworks
• Practical experience with OpenAI, Anthropic, Google Gemini, Amazon Bedrock, or similar AI platforms
• Strong system design and problem-solving skills
• Upper-Intermediate English (B2+) or higher 

Nice to Have

• Experience with AWS and cloud-native applications
• Exposure to MCP, AI automation, or multimodal AI 

Responsibilities

• Build AI-powered features using modern LLMs
• Develop AI agents, tool-calling workflows, and RAG systems
• Integrate AI capabilities with enterprise products through APIs and MCP
• Optimize prompts, model performance, and AI quality
• Collaborate with Product, Engineering, and Design teams to deliver production-ready AI solutions 

What We Offer

• Work on production AI features with real user impact in a flexible, Agile, multinational team where innovation and collaboration drive everything we do
• Continuous learning and professional growth alongside top talent in the global tech industry
• Hybrid work model, combining remote work with time in our Lviv office
• Daily collaboration with native English speakers, providing a natural opportunity to strengthen your English in a professional environment
• 18 working days of paid vacation, 10 working days of paid sick leave, and 11 paid Ukrainian public holidays

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. 

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

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

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

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

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

Our benefits to you:

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

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

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

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

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

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

🎯Rewards program for mentoring and coaching colleagues

✈️In-house Travel Service

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

🎳Other benefits could be added based on your location 

About the Role
We are seeking an AI & Data Science Consultant to drive the discovery, strategy, and end-to-end delivery of advanced AI initiatives for EPAM’s global clients. This role is a unique hybrid, blending strategic business consulting with deep practical engineering. You will collaborate directly with client executives and EPAM’s delivery teams to transform complex business challenges into scalable, production-ready AI, Machine Learning, and Agentic solutions.
 

Key Responsibilities

• Consult & Strategize: Lead client-facing discovery sessions and workshops to identify high-value AI opportunities, define MVP scopes, and map out strategic delivery roadmaps.
• Design & Architect: Shape scalable AI products incorporating Generative AI, RAG, multi-agent frameworks, semantic layers, and advanced analytics.
• Bridge the Collaboration: Serve as the central link connecting business stakeholders, data scientists, ML engineers, DevOps, and product teams.
• Drive Delivery & MLOps: Apply a strong engineering mindset to ensure solutions are secure, production-ready, and smoothly integrated into cloud infrastructures.
• Support Business Growth: Partner on pre-sales activities, solution estimation, and proposal development while contributing to EPAM’s internal AI and MLOps offerings.
   

Requirements

• Professional Experience: 3+ years of hands-on experience in Data Science, ML, or Applied AI, with a proven track record of bringing models from concept to production.
• Consulting & Communication: Strong active listening, presentation, and storytelling skills; ability to confidently translate complex AI concepts for C-level stakeholders.
• AI & Agentic Tech Stack: Experience with RAG, LLM applications, multi-agent orchestration, and tools like LangChain, LangGraph, CrewAI, LlamaIndex, or Vector DBs.
• Data & Architecture: Understanding of Semantic Layers, metadata, knowledge graphs, and data platforms (such as Databricks or Snowflake).
• Engineering & MLOps: Familiarity with the production model lifecycle, MLOps/LLMOps pipelines, and cloud platform integrations.
   

Nice to Have

• Experience mentoring cross-functional AI teams or driving enterprise-scale GenAI adoption.
• Practical knowledge of cloud infrastructure and DevOps tooling.
• Insights into AI governance and ethical AI frameworks.

About Logivations

Adidas, DHL, IKEA, Heineken, Mercedes, Swarovski — and 30,000+ other users — work with software built by Logivations. We develop cloud-native solutions using cutting-edge technologies to transform logistics and operations worldwide. Learn more at www.logivations.com.

The Role

We are looking for a detail-oriented Junior Data Annotator to join our AI/ML team in Lviv. Your work will directly contribute to the quality of machine learning models used by leading global companies. No programming background is required — what matters is sharp analytical thinking, precision, and the ability to follow structured guidelines consistently.

This is an excellent entry-level opportunity for someone eager to step into the IT world and grow within an international tech environment.

What You’ll Do

• Annotate and label datasets according to project-specific guidelines
• Review, validate, and correct annotations to ensure quality and consistency
• Identify edge cases and inconsistencies in data
• Collaborate with the data team to resolve ambiguities and refine processes
• Maintain productivity and quality metrics
• Adapt to evolving annotation techniques, tools, and project requirements

What You Bring

• English reading comprehension at B1 level or above
• High school diploma or equivalent or a student
• Basic to intermediate computer proficiency
• Strong attention to detail and analytical mindset
• Ability to work independently, manage time effectively, and meet deadlines
• Comfort with structured, rule-based, and repetitive tasks
• Clear communication skills for cross-functional collaboration

Nice to Have

• Prior experience in data annotation, data review, or a related field
• Ability to identify patterns and edge cases in data

What We Offer

• Decent compensation paid in EUR
• Hybrid schedule (office and remote)
• Direct impact on international AI/ML projects
• Professional growth through training and cross-functional collaboration

How to Apply

Please send your CV in English.

We are looking for Computer Vision Engineers with strong experience in classical and geometric computer vision, and hands-on experience with SLAM, Visual-Inertial Odometry (VIO), or related localization systems.

We are open to candidates of different seniority levels (Junior to Senior), with responsibilities and scope defined by experience.

Responsibilities:

• Develop and optimize classical and geometric computer vision algorithms
• Work with feature tracking, matching, and geometric processing
• Contribute to SLAM / VIO pipeline components
• Integrate and test multi-sensor fusion systems (camera + IMU)
• Design and run experiments, evaluate algorithm performance
• Translate research papers into practical implementations
• Collaborate with cross-functional engineering teams

Required Qualifications:

• Hands-on experience with classical computer vision
• Understanding of geometric computer vision concepts, including camera models, feature detection, and tracking
• Familiarity with SLAM and/or Visual-Inertial Odometry (VIO) concepts
• Experience with C++ and Linux environments
• Ability to design, implement, and optimize computer vision algorithms in practice
• Ability to learn from and implement research-based methods
• Degree or ongoing studies in Computer Science, Mathematics, Physics, Engineering, or a related STEM field

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems
• Robotics or navigation background

We are looking for a Computer Vision Engineer with strong experience in deep learning and production computer vision systems.

The role involves developing and bringing computer vision models into production, covering the full lifecycle from training and evaluation to deployment and system integration.

Responsibilities:

• Develop and improve Computer Vision and Machine Learning models
• Design and implement solutions for object detection, classification, segmentation, and tracking
• Work with large-scale image, video, and telemetry datasets
• Prepare, process, and maintain datasets for model training and evaluation
• Manage model training, validation, and testing workflows
• Optimize models for production deployment and real-time performance
• Integrate ML models into software services, applications, and APIs
• Analyze model performance and identify opportunities for quality improvement
• Participate in the design and architecture of AI components within the product ecosystem
• Collaborate closely with Backend, Infrastructure, Data, and Product Engineering teams
• Contribute to the development of MLOps practices and the end-to-end machine learning lifecycle.

Requirements:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience working with thermal imaging data (thermal cameras, infrared imagery) would be an advantage
• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding its team in Central Europe and is looking for talented Data Science Engineers to join us. Our projects span multiple domains, including data analysis, fintech, computer vision, image processing, edge-device solutions, Large Language Models (LLMs), and classical Machine Learning applications. We build custom Data Science solutions for clients across various industries, combining strong engineering practices with a research-driven mindset.

Joining Quantum means becoming part of a team that values solid technical fundamentals, continuous learning, and practical problem-solving. You'll collaborate on impactful products, work with cutting-edge technologies, and contribute to projects that turn complex ideas into real-world solutions.

Must have skills:

• 3+ years of commercial DS/ML experience
• Solid foundation in linear algebra, statistics, and probability
• Strong Python, including NumPy, Pandas, and scikit-learn
• Hands-on experience with PyTorch (or TensorFlow)
• Deep experience in at least one of: 
  • Computer Vision (modern DL: detection, segmentation, classification - ViT, YOLO, SAM); 
  • LLMs / NLP (fine-tuning, RAG, prompt engineering, embeddings, evaluation); 
  • Classical ML at scale (tabular, time series, recommender systems)
• Working knowledge of Transformers and attention; familiarity with CNNs
• Experience deploying models to production (Docker, REST/gRPC serving, basic monitoring)
• Experience with at least one cloud platform (AWS, GCP, or Azure)
• Clean code and Git workflow
• Experience with SQL
• Upper-Intermediate English (B2+) - you'll communicate directly with clients

Nice to have skills:

• Cross-domain exposure: if your main strength is CV, some LLM exposure is a plus (and vice versa)
• Edge deployment: TensorRT, OpenVINO, ONNX, quantisation, model distillation, mobile/embedded inference
• LLM tooling: LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LoRA/QLoRA fine-tuning, agentic frameworks
• MLOps & model monitoring: MLflow, DVC, Weights & Biases, CI/CD for ML
• Classical CV with OpenCV (still relevant for hybrid pipelines and edge work)
• Ability to read recent papers and implement methods in new domains
• Experience working with external clients
• Participation in Kaggle competitions

Your tasks will include:

• Own full-cycle DS projects: scoping with the client, data prep, modelling, evaluation, deployment
• Build solutions across CV, LLM/NLP, and classical ML depending on the project pipeline
• Deploy models to production - cloud, edge, or hybrid, depending on client needs
• Read recent research and adapt methods to client problems
• Communicate technical decisions and trade-offs directly to clients

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

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!

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.

You'll be a great fit if you have:
• 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;
• Bachelor's degree in Computer Science or a related field.

What you'll do:
• 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 ensure your growth with:

• Competitive salary fixed in USD;

• Flexible working schedule and fully remote work format;

• Paid vacation days and sick leave days;

• Personal and professional development opportunities;

• Participation in building innovative projects from scratch using modern technologies;

• Team-building activities and corporate events;

• English classes and educational events.

We are looking for a Computer Vision Engineer with strong experience in deep learning and applied computer vision systems.
The role involves working on challenging CV problems in real-world environments.
We consider Middle and Senior engineers, with scope adapted to experience.
Responsibilities

• Develop, train, and optimize deep learning models for:
  • image retrieval
  • image matching (keypoint detection and matching)
  • auxiliary perception tasks supporting the main pipeline
• Evaluate models using quantitative metrics, including:
  • retrieval quality (mAP, Recall@K)
  • matching performance (precision/recall, repeatability)
  • end-to-end system metrics (accuracy, latency, robustness)
• Optimize models for production deployment using modern toolchains:
  • ONNX / TensorRT / OpenVINO / edge acceleration where applicable
  • model compression techniques (quantization, pruning, distillation)
  • latency, memory, and throughput optimization
• Work with large-scale visual datasets and descriptor-based representations
• Collaborate with engineering teams to integrate models into production systems

Required Qualifications

• 2–4+ years of experience in Computer Vision / Deep Learning
• Hands-on experience with keypoint detection and matching models (e.g. SuperPoint, R2D2, DISK, LightGlue, SuperGlue)
• Experience with image retrieval or metric learning systems
• Strong understanding of geometric and motion-related computer vision concepts:
  • keypoint detection and description
  • image matching and geometric verification (RANSAC, homography, PnP)
  • pose estimation and refinement techniques (PnP, bundle adjustment, pose graph optimization)
  • optical flow and frame-to-frame tracking
  • vector search / ANN methods for descriptor retrieval
• Strong Python skills (PyTorch and scientific computing stack)
• Ability to read and understand inference code in C++

Nice to Have

• Experience with noisy or imperfect real-world datasets
• Self-supervised or unsupervised learning methods (contrastive learning, homography supervision, etc.)
• Experience optimizing models for edge deployment (quantization, pruning, distillation)
• Familiarity with FAISS or similar vector search systems
• Experience with optimization libraries for geometric problems (bundle adjustment, pose refinement)
• Understanding of real-time constraints (latency, memory, CPU inference budgets on ARM or low-power x86 systems)

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

Key Responsibilities:

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

Required Skills:

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

Nice to Have:

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

We offer*:

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

* benefits package is not applicable for freelancers

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.   
 

At Fozzy Group, we are developing a next-generation Decision Support System that connects operational, commercial, and investment data to optimize financial effectiveness and drive guest experience. As a Data Scientist you will own the measurement layer to derive Initiative & Investment Performance Insights. The role 

is organized around three streams: 

• Effect Measurement & Causal Inference: quantify the true incremental impact of initiatives using A/B testing and quasi-experimental methods. Measure uplift in purchase frequency, guest spend, average check, and retention against properly designed control groups, and form clear conclusions on whether an initiative works and is worth its cost. 

• Driver & Heterogeneity Analysis: identify the most significant factors of project performance using ML: guest profile structure and dynamics, technology presence, assortment, distance to competitors – so the business can assess project potential per store, forecast effects, and scale more effectively. 

• Self-Service Validation & Monitoring: build reusable, automated frameworks for effect validation and monitoring that let Finance and business owners get verified answers on demand, with full source transparency and reproducibility.
You will join a cross-functional team to design and implement data-driven decision module that directly influence financial outcomes. 

Job Responsibilities 

• Design and run experiments (A/B tests) and quasi-experiments (difference-in-differences, synthetic control, propensity score matching), and apply causal ML to estimate the incremental and heterogeneous effects of operational, commercial, and investment initiatives. 

• Build uplift / heterogeneous-treatment-effect models to learn which guests, segments, and stores respond most, and quantify effects on key metrics – purchase frequency, share-of-wallet / guest spend, average check, CLV, and retention (via survival models) – for pilot versus control groups. 

• Develop interpretable driver models (gradient boosting with SHAP, causal forests) that explain project performance, and rank the factors with the highest impact on results. 

• Build store-level potential-scoring and effect-forecasting models – probabilistic and hierarchical forecasting, transfer learning and store embeddings to borrow signal across the network – to guide and prioritize scaling decisions. 

• Design adaptive early-stop logic using Bayesian sequential testing, multi-armed bandits, and change point detection, to reallocate or halt rollouts as soon as the economic signal turns marginal. 

• Translate financial and commercial questions into statistically rigorous measurement designs, and connect statistical results to economic value (incrementality, ROI, payback). 

• Build SQL and Python pipelines, reusable feature sets / a feature store, and a self-service experimentation framework. 

• Productionize and monitor models (MLOps) – drift detection, automated validation, reproducibility, and source transparency. 

• Partner with Finance, Investment, Commercial, and Operations teams to deliver verified, decision ready insights. 
 

Requirements 

• Bachelor’s Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance; 

• At least 2 years working experience on Data Science; 

• Strong foundation in Statistics, Causal Inference, and Experimental Design – A/B testing, Hypothesis Testing, Power Analysis; 

• Proven experience with SQL (Window functions, CTEs, joins) and Python; 

• Expertise in Machine Learning, Time Series Analysis; 

• Ability to work independently and decompose complex problems. 
 

Preferred 

• Experience with Airflow, Docker, or Kubernetes for Data Orchestration; 

• Practical experience with Amazon SageMaker: training, deploying, and monitoring ML models in a production environment; 

• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Looker); 

• Ability to design and deliver packaged analytical/ML solutions. 
 

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.