Jobs Data Science

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

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

Key Responsibilities

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

Requirements

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

Nice to Have

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

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

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

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

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

Job Responsibilities:

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

Requirements:

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

Skills:

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

Nice to have:

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

What We Offer:

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

About the Company

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

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

What You'll Be Doing

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

Requirements

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

What We Offer

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

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

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

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

Why Join the Team:

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

Key Requirements:

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

Nice to Have:

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

Key Responsibilities:

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

What We Offer:

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

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


Requirements:

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

Responsibilities:

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

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

What you will do: 

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

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

   

What we expect:

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

🚀We are looking for an experienced Data Scientist for a full-time job to join our team.


🎯 Requirements:
-2+ years of experience as a data scientist
-BSc in Mathematics, Statistics, Computer Science, Economics, or another related field.
-Experience in using Python & SQL
-Experience with Airflow and GCP
-Experience with Git & CI/CD
-Upper Intermediate English — written and spoken
-Ability to design creative solutions for complex requirements
-Ability to learn and lead projects independently, and to work with minimal supervision with customers (tech & business)

🧩 Responsibilities:
-Conduct independent research, including defining research problems, creating research plans, designing experiments, developing algorithms, implementing code, and performing comprehensive comparisons against existing benchmarks;
-Clearly communicate your research findings to both technical and non-technical audiences
-Work on various data sources and apply sophisticated feature engineering capabilities
-Bring and use business knowledge
-Build and manage technical relationships with customers and partners.

🎯 We offer:

• Paid vacation and sick leave
• We provide the equipment you need to work comfortably (if required)
• We cover 50% of courses if you want to grow professionally
• Regular salary reviews based on your performance
• Competitive salary, depending on your experience
• Always on-time payments — no delays
• A normal, supportive team without unnecessary bureaucracy

The product we are working on is one of TOP-3 navigation systems, complex web-services and other solutions related to it. The web and mobile apps handle information at massive scale and extend well beyond the search giving people and companies a lot of new useful options.

As a Data Science Infrastructure Software Engineer, you will play a high-impact role within a small, efficient team dedicated to bridging the gap between Engineering and Data Science. Your work will focus on building cutting-edge Generative AI infrastructures and frameworks that significantly boost productivity across the whole product. You will develop tools that bring engineering rigor to data science workflows, solving complex problems in the GenAI space that the market has yet to crack. This is a high-impact role in a small team. You will be working alongside talented engineers and data scientists to build productivity-defining products for the next generation of the application.

Responsibilities:

• GenAI Development: Design, develop, and maintain features for our GenAI analytics agent (DataWhiz) that serve the entire organization for complex data analytical inquiries.
• Framework Optimization: Improve and scale the internal GenAI framework, including fixing bugs and optimizing the core engine for performance and reliability.
• UI/UX Enhancement: Build and implement new UI features for the GenAI chat interface to ensure a seamless experience for internal stakeholders.
• Cross-Functional Collaboration: Partner with development, product, and UX teams to define product requirements, while collaborating with core platform engineers to ensure infrastructure alignment.

• Engineering Excellence: Bridge the gap between Engineering and Data Science by applying software engineering best practices (code reviews, CI/CD, scalability) to DS workflows.

   

Requirements:

• Location in Warsaw
• 5+ years of experience in software development, with a focus on infrastructure or data-centric applications.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
• Strong proficiency in Python and a solid understanding of backend architecture.
• Experience with SQL and the ability to handle complex data structures.
• Problem-Solving: Ability to write clean, abstract, and maintainable code for a rapidly evolving GenAI landscape.
• Communication: Excellent communication skills for collaborating with geographically distributed teams and translating data science needs into technical requirements.

• Fluency in English.

   

Nice to have:

• Generative AI Expertise: Familiarity with LLM orchestration frameworks, prompt engineering, or vector databases.
• Polyglot Programming: Experience with Kotlin, Java, Bash, or HCL (Terraform).
• Frontend Interest: Experience building chat interfaces or data visualization dashboards.

• Large-Scale Systems: Experience working on large-scale infrastructure that serves a diverse range of internal or external users.

   

We offer:

• Opportunities to develop in various areas;
• Compensation package (20 paid vacation days, paid sick leaves);
• Flexible working hours;
• Medical Insurance;
• English courses with a native speaker, yoga (zoom);
• Paid tech training and other activities for professional growth;
• Hybrid work mode (∼3 days in the office);
• International business trips

• Comfortable office.

   

If your qualifications and experience match the requirements of the position, our recruitment team will reach out to you in a week maximum. Please rest assured that we carefully consider each candidate, but due to the amount of applications the review and further processing of your candidacy may take some time.

Role Type: Contract / Fixed-Scope Consulting Engagement
Duration: 2–3 months (10–12 weeks)
Allocation: Full-time or near full-time (4–5 days/week preferred)
Location: Remote (Must overlap with Spain / CET ± 6 hours)
Languages Required: Spanish (C1+) and English (B2+)
 

The Opportunity

We are looking for a hands-on Senior Data Science / Analytics Engineering Consultant to audit, redesign, and rebuild our core chargeback estimation and revenue estimation models.

This is a critical, end-to-end project. You will turn existing prototypes into production-grade pipelines within our modern data stack (dbt on Databricks & Python). Additionally, you will design and build a lightweight, business-facing scenario tool that enables finance and operations stakeholders to run “what-if” revenue simulations.

Our Technical Philosophy: Parsimony Over Black Boxes

We explicitly favor simple, highly interpretable, parametric approaches. If your first instinct for a forecasting problem is to throw an XGBoost ensemble, a deep learning model, or an LLM at it, this is not the project for you.

We build models where every parameter carries an explicit business meaning that can be explained to non-technical stakeholders in plain language (e.g., “If price increases by 10%, conversion drops by X% because our calculated price elasticity is −1.3”).
 

Scope of Work & Deliverables

• Phase 1: Discovery & Audit (Weeks 1–2): Review current estimation models (assumptions, dbt lineage, validation methods). Reconcile historical model outputs against actual accounting figures for the last 12–24 months to quantify bias and error. Deliver a written findings report.
• Phase 2: Redesign (Weeks 3–4): Propose the target parametric methodology for each model (granularity, refresh cadence, uncertainty quantification) and secure stakeholder sign-off.
• Phase 3: Rebuild (Weeks 5–9): Productionize the new models in dbt, Databricks, and Python. Use curve-based formulations with fitted historical parameters and clear confidence intervals. Implement strict unit/dbt testing and MLflow tracking.
• Phase 4: Scenario Tool (Weeks 9–10): Build a lightweight business interface (e.g., Streamlit on Databricks or a parameterized Databricks SQL dashboard). Users must be able to input hypotheses (price ±X%, volume ±Y%, mix shifts) and instantly view projected net impact with uncertainty bands.
• Phase 5: Handover (Weeks 11–12): Conduct knowledge transfer sessions, deliver runbooks/model cards, and provide a 2-week post-handover bug-fix support window.
   

Your Profile

• Experience: 5–8+ years in Data Science, Quant Analytics, or Senior Analytics Engineering.
• Production Ownership: Proven track record of owning financial-estimation or forecasting models in production end-to-end.
• The “Parsimony” Mindset: Demonstrable expertise in parametric/curve-based modeling (price elasticity, cohort survival curves, demand curves, GLMs) over black-box ML.
• Stakeholder Tooling: Experience building clean “what-if” tools or financial planning interfaces for business leadership.
• The Stack: Advanced Python (pandas, numpy, scikit-learn, statsmodels, and/or scipy.optimize), production dbt (incremental models, snapshots, tests), and Databricks (PySpark, Delta, workflows).
• Domain Knowledge: Direct experience in payment risk, chargebacks, refund/dispute modeling, revenue forecasting, cohort LTV, or pricing analytics.
• Communication: Exceptional ability to cross-reference data science outputs with strict financial accounting figures.
• Languages: Spanish (C1+) is mandatory for daily synchronization with local finance/ops teams; English (B2+) is required for technical documentation.
   

Nice to Have

• Background in FinTech, subscription models, payments, or high-volume e-commerce.
• Deep familiarity with Unity Catalog, Databricks Workflows, or Airflow.
• A strong track record of successful independent consulting engagements (references requested).

We are looking for a Senior AI/Machine Learning Engineer to join a healthcare project from the Netherlands focused on simplifying preparation for orthopedic surgeries. The product uses artificial intelligence to automatically analyze 3D images of the skeletal system and support surgical planning. In this role, you will focus on continuing and improving the X3D pipeline (X-ray to 3D bone reconstruction) and integrating it into the web application.
 

Requirements:
— 5+ years of commercial experience in Machine Learning/AI engineering.
— Proven commercial experience working on medical imaging or healthcare-related projects is a must.
— Strong experience with PyTorch and deep learning model training, evaluation, and optimization.
— Solid background in medical image analysis (CT, X-ray) and/or 3D computer vision.
— Strong understanding of image processing fundamentals, including registration, segmentation, and data augmentation techniques.
— Familiarity with GAN architectures (Pix2Pix, CycleGAN) and encoder-decoder networks.
— Experience working with medical imaging file formats (NIfTI, DICOM).
— Ability to read and implement techniques from research papers.
— Proficiency in Python and scientific computing libraries (NumPy, SciPy, SimpleITK or similar).
— Self-directed and independent working style with the ability to effectively collaborate under technical guidance.
— Upper-Intermediate or higher level of English (spoken and written).

Nice to have:
— Experience with 3D shape reconstruction or 3D mesh processing.
— Familiarity with DRR generation from CT volumes.
— Experience with Azure ML or similar cloud ML platforms.
— Background in orthopedic or musculoskeletal imaging.
— Experience in a medical device or regulated environment (FDA, CE).

Responsibilities:
— Improve and extend the existing X3D pipeline for X-ray to 3D bone reconstruction.
— Design, train, evaluate, and optimize deep learning models for medical image analysis and 3D reconstruction tasks.
— Work with medical imaging data (CT, X-ray, DICOM, NIfTI) and implement preprocessing, augmentation, segmentation, and registration techniques.
— Research, prototype, and implement new approaches from academic papers and industry best practices.
— Integrate machine learning solutions into the web application and support deployment workflows.
— Collaborate closely with the Head of Engineering to further develop and productionize the existing AI pipeline.
— Maintain code quality through testing, documentation, and continuous improvement of ML infrastructure and development processes.

Interview stages:
— HR interview (30 minutes).
— Technical interview (1 hour).
— Interview with the customer (1 hour).
— Job offer 🎉🎉🎉

We offer:
— Competitive salary.
— Challenging tasks and projects.
— Opportunities for professional development and growth.
— Flexible working hours.
— New hardware.
— Free English lessons.
— Table tennis and yoga classes.
— Availability of generators and Starlinks in the office.
— Small gym in the office.
— Adjustable height tables.
— Regular office fruit delivery and other benefits.

Let’s create value together!

Mine Marketing works on the connection between advertising, data, and automation. We’re looking for a Technical Data & Automation Specialist to join our team and work closely with leadership on data, automation, system development, troubleshooting, and production operations.


What you will do with us:
- Connect advertising systems with internal data systems
- Build and improve pipelines that handle bulk in real time 
- Dig deep into performance issues and translate data into business decisions 

What we're looking for 🎯
- Hands-on experience with Claude Code and building automations
-High command of SQL: complex queries, optimization, performance thinking 
- Understanding of Data Pipelines, ETL, and Data Processing Processes
- Familiarity with performance metrics: ROI, CPA, CTR and the ability to connect data to decisions
- Analytical, entrepreneurial thinking, and true independence in complex tasks

Significant Advantage
- Experience in production systems in the advertising / performance worlds
- Working with Meta Ads/Google Ads (APIs)
- AWS/GCP experience

What awaits you ✨
- Real data that drives business decisions
- Real technical challenges: scale, reliability, accuracy 
- Lots of ownership and freedom to move things fast


What we offer:
- Opportunities for professional development and personal growth 🚀

- Competitive salary, reasonable and fair working conditions 💵

- A ridiculously awesome team and work environment 🎉

- Training opportunities, including paid courses and webinars 💻

- Remote working conditions 🏠

- Generous PTO and Holidays 🌴

Join us and let's make some social media magic happen! Apply now!

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

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 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 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++

Our Enterprise Banking client is enhancing their Regulatory Reporting Value Stream and seeks a strategic Data Steward to own data governance, ensure compliance, and maintain the integrity of critical financial data. You will serve as the primary liaison between business stakeholders and technical teams to ensure data accuracy across products, systems, and processes.

Core Responsibilities

• Data Governance Leadership: Own and drive end-to-end data governance and quality frameworks; ensure full compliance with internal standards and external regulatory requirements.
• Architectural Stewardship: Maintain business glossaries, metadata repositories, and data quality rules; design robust data mappings and transformation logic.
• Requirements Engineering: Translate complex business/regulatory needs into clear functional specifications for engineering teams.
• Quality Remediation: Perform root cause analysis on data quality incidents and coordinate cross-functional remediation efforts.
• Strategic Insights: Develop KPIs and performance dashboards to provide stakeholders with actionable data trends and business intelligence.

What We Need

• Expertise: Significant professional experience in Data Governance, Data Stewardship, or Technical Business Analysis.
• Domain Knowledge: Solid grounding in banking/financial services products and regulatory reporting workflows.
• Technical Proficiency: Advanced SQL skills for large-scale data analysis, profiling, and structural mapping; deep understanding of data warehousing principles.
• Collaboration: Proven ability to act as the "connective tissue" between business units and IT delivery teams.
• Tooling: Proficiency in JIRA, Confluence, and the MS Office suite.

ПРО ПОЗИЦІЮ

Вимоги:

• Досвід DS/MLE від 1 року
• Математичний бекграунд: вища математична освіта (КПІ ІПСА, МехМат Шевченко тощо), бажано олімпіадний досвід
• Глибокі знання алгоритмів і структур даних, глибоке розуміння ООП, глибокі теоретичні та практичні знання машинного та глибокого навчання
• Практичний досвід вирішення NLP та Tabular Data ML задач
• Високий рівень володіння Python, включаючи досвід роботи з бібліотеками машинного навчання і володіння принаймні одним із фреймворків глибокого навчання (Tensorflow, Keras, PyTorch)
• Вміння писати чистий, підтримуваний та ефективний код, готовий до production
• Вміння трансформувати бізнес-вимоги у технічні завдання для ML-рішень
• Досвід feature engineering
• Досвід роботи з Git та Docker
• Досвід роботи з базами даних (SQL/NoSQL) для отримання та підготовки даних для моделей

Буде плюсом:

• Досвід вирішення CV завдань
• Досвід успішних виступів на хакатонах/Kaggle
• Досвід роботи з Airflow на рівні запуску та моніторингу завдань
• Розуміння принципів паралелізму в Python та досвід роботи з відповідними бібліотеками

Приклади задач:

• Підвищення точності поточних CV, NLP та інших моделей
• Розробка нових моделей з нуля: від R&D та feature engineering до валідації
• Аналіз великих обсягів даних для пошуку інсайтів та формулювання гіпотез для моделювання