Jobs Data Science

If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cuttingedge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Start.io is a mobile data platform that enables organizations to uncover insights and make datadriven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team.

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities;
• Develop and own end-to-end highly scalable data pipelines;
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
• Provisioning data models for real-time (online) processing;
• Shape new data products, and constantly improve the existing products;
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions;
• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.

Requirements:

• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• 6 years as a Data Scientist - a strong background in ML concepts and models;
• Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.;
• Understanding of databases and SQL for data retrieval;
• Monitoring and alerting tools (e.g. Grafana, Kibana).

Will be a plus:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage;
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
• Experience with PMML.

What we offer:

• Help and support from our caring HR team;
• 20 days of vacation;
• The exchange of experience and work with talented colleagues;
• Last but not least - valuable compensation for your efforts.

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a Senior Data Scientist to develop predictive models and quantitative analytics that power risk-based vulnerability prioritization within a large-scale enterprise security program. You will structure and analyze massive security telemetry datasets, build ML algorithms to eliminate scanning noise and false positives, and establish unified data dashboards to drive adoption of data-driven security governance. The role requires 5+ years of data science experience with direct commercial application to vulnerability management, operating with full autonomy.

What you will do

• Develop predictive models and quantitative analytics to prioritize vulnerabilities based on contextual risk and business impact;
• Structure and analyze massive outputs of security data from across the enterprise ecosystem to support the ASPM framework;
• Create machine learning algorithms or statistical models to automatically identify and filter out scanning noise and false positives;
• Establish a unified data delivery structure and dashboards to drive the adoption of data-driven security governance.

Must haves

• 5+ years of commercial data science experience, operating completely autonomously with no required supervision;
• Advanced proficiency in Python, R, and SQL;
• Experience with machine learning frameworks such as TensorFlow and PyTorch;
• Experience with data visualization tools;
• Commercial experience applying data science to vulnerability management;
• Upper-intermediate English level.

Nice to haves

• Familiarity with Cloud Security Posture Management (CSPM) data outputs (e.g., Wiz).

The benefits of joining us

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
• Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates

If it’s a match — you’ll get an offer!

Join Sigma Software to help build advanced machine learning solutions for one of the large-scale players in the programmatic advertising ecosystem. We are looking for a Senior Machine Learning Engineer with strong production ML expertise and deep interest in real-time optimization systems, large-scale behavioral data, and AdTech challenges.

In this role, you will work with a dedicated Sigma Software team on a predictive modeling platform integrated with a live ad exchange processing hundreds of millions of auction requests daily. You will contribute to sophisticated ML solutions involving bid optimization, calibration, counterfactual evaluation, and constrained decision-making systems.

We as a company offer the opportunity to work on technically challenging products, collaborate with experienced engineers and data scientists, and make a direct impact on large-scale production systems.

CUSTOMER

Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a high-scale ad exchange platform and is investing in predictive decisioning capabilities to improve advertising performance, audience targeting, and campaign optimization through advanced machine learning technologies.

PROJECT

The project focuses on building a predictive modeling and optimization platform on top of a live ad exchange environment. The platform evaluates and filters advertising supply in real time, predicts high-performing audience contexts, builds look-alike audiences from small seed datasets, and optimizes campaign performance across multiple business objectives and operational constraints.

The team works on complex machine learning challenges including censored bid-landscape modeling, sparse and delayed conversion attribution, calibration systems, counterfactual evaluation, and constrained optimization models. The solution is designed for large-scale production use and close collaboration with the Customer’s internal data science organization.

Job Description

• Build and improve censored bid-landscape models to estimate clearing-price distributions from partially observed auction data
•  Develop real-time win probability estimation models responsive to bid pricing dynamics
• Design and implement hierarchical lift estimation models with confidence-bound-based selection strategies
• Build conversion propensity models using sparse, delayed, and aggregate-only labels
• Develop look-alike audience modeling approaches using positive-unlabeled learning and embedding-based nearest-neighbor techniques
• Implement advertiser-level calibration strategies while independently monitoring ranking and calibration quality
• Design robust offline evaluation frameworks using inverse-propensity scoring, doubly-robust estimators, and importance reweighting
• Define exploration strategies and propensity logging approaches to ensure reliable downstream correction and evaluation
• Develop constrained optimization mechanisms for campaign objectives, pricing constraints, and volume targeting
• Contribute to data diagnostics, capability assessments, and evidence-based model recommendations
• Collaborate with the Customer team during post-launch tuning and performance validation cycles
• Prepare technical documentation and knowledge transfer materials for the Customer’s internal data science team
• Participate in architecture discussions and contribute to scalable ML platform design decisions

Qualifications

• 5+ years of experience in Machine Learning or Data Science with production-grade models measured against business KPIs
• Strong Python skills including numpy, pandas, and scikit-learn
• Strong SQL skills and experience working with large-scale datasets
• Deep practical experience with XGBoost, LightGBM, or CatBoost
• Strong understanding of regularization, calibration methods, and categorical feature handling
• Strong knowledge of probability, statistics, confidence intervals, and statistical power analysis
• Experience with feature engineering for structured and behavioral datasets
• Hands-on experience with Spark or PySpark
• Practical knowledge of experimentation frameworks and A/B testing methodologies
• Experience with advanced validation approaches including temporal splits, leakage detection, drift analysis, and slice-based metrics
• Understanding of explainability techniques such as SHAP and permutation importance
• Upper-Intermediate English level or higher

WILL BE A PLUS

• Experience in AdTech modeling including CTR/CVR prediction, bid-landscape modeling, audience segmentation, and RTB mechanics
• Experience working with sparse, delayed, or censored labels
• Knowledge of attribution modeling, survival analysis, and positive-unlabeled learning
• Practical experience with counterfactual and off-policy evaluation techniques
• Understanding of calibration methods including isotonic regression and Platt scaling
• Experience with hierarchical, empirical-Bayes, or partial-pooling models
• Knowledge of constrained or multi-objective optimization approaches
• Experience with uplift modeling and causal inference methods
• Experience with Vertex AI or similar managed ML training environments
• Publications, competitive modeling achievements, or open-source contributions related to Machine Learning or AdTech

PERSONAL PROFILE

• Strong analytical and problem-solving skills
• Ability to work effectively in a highly data-driven environment
• Strong communication and stakeholder management abilities
• Ability to explain complex modeling decisions to technical and non-technical audiences
• Proactive mindset with strong ownership mentality
• Attention to detail and scientific rigor in experimentation and evaluation

About the Role

Trialt is expanding its Statistical Programming team to support international Phase I-IV clinical trials across a range of therapeutic areas. Our programmers work on projects for pharmaceutical, biotechnology, medical device and CRO clients across the US and Europe. Depending on the project and individual experience, you may join a client-dedicated assignment or work within a full-service biometrics team. Project assignments are based on your experience, expertise and current business needs.

What You Will Do

• Lead statistical programming activities across one or more clinical studies.

• Oversee the development and validation of SDTM, ADaM and TLF deliverables.

• Plan programming work, estimate timelines and coordinate task allocation.

• Review complex deliverables and ensure compliance with project, CDISC and regulatory requirements.

• Maintain traceability from source data through SDTM and ADaM to final statistical outputs.

• Support the preparation and review of Define-XML, aCRF, SDRG, ADRG and validation reports.

• Investigate and resolve complex programming, data and submission-readiness issues.

• Lead client-facing meetings and technical discussions.

• Monitor project quality, timelines, risks and programming status.

• Mentor programmers and provide technical leadership.

• Collaborate closely with biostatistics, data management, medical writing and project management teams.

Required Qualifications

• Extensive statistical programming experience within clinical research.

• Advanced SAS programming skills and strong knowledge of CDISC SDTM and ADaM standards.

• Extensive experience producing and independently reviewing SDTM, ADaM and TLF deliverables.

• Experience leading programming activities at study or project level.

• Strong understanding of regulatory submission requirements and end-to-end traceability.

• Experience reviewing submission documentation and resolving Pinnacle 21 findings.

• Ability to plan work, estimate timelines, oversee quality and manage programming risks.

• Strong client-facing communication and technical leadership skills.

• Ability to mentor programmers and make independent technical decisions.

• English at Upper-Intermediate level or higher.

About the Role

Trialt is expanding its Statistical Programming team to support international Phase I-IV clinical trials across a range of therapeutic areas. Our programmers work on projects for pharmaceutical, biotechnology, medical device and CRO clients across the US and Europe. Depending on the project and individual experience, you may join a client-dedicated assignment or work within a full-service biometrics team. Project assignments are based on your experience, expertise and current business needs.

What You Will Do

• Independently develop and validate SDTM and ADaM datasets.

• Produce and QC complex tables, listings and figures.

• Interpret protocols, SAPs, dataset specifications and mock shells.

• Take ownership of programming activities for an assigned study or workstream.

• Review deliverables produced by other programmers and provide technical guidance.

• Investigate data issues, SAS log findings and validation findings.

• Support submission deliverables and study documentation.

• Estimate tasks, monitor timelines and communicate project status.

• Participate in client meetings and technical discussions.

• Collaborate with biostatisticians, data managers, medical writers and project teams.

Required Qualifications

• Solid statistical programming experience within clinical research.

• Strong SAS programming skills, including DATA Step, PROC SQL and SAS Macro Language.

• Hands-on experience with SDTM, ADaM and TLF production and QC.

• Strong working knowledge of CDISC standards and controlled terminology.

• Understanding of traceability from source data through SDTM and ADaM to statistical outputs.

• Ability to work independently with protocols, SAPs, specifications and study documentation.

• Ability to manage programming activities for an assigned study or workstream.

• Strong communication, organisation and problem-solving skills.

• English at Upper-Intermediate level or higher.

Strong Pluses

• Previous experience as a Lead Programmer or readiness to take programming ownership.

• Experience with Define-XML, aCRF, SDRG and ADRG.

• Experience using Pinnacle 21 or similar validation tools.

• Experience supporting regulatory submissions.

• Experience with R or Python.

• Previous experience in an international CRO, FSP or sponsor environment.

Working Model

• Fully remote position.

• Full-time engagement.

• Long-term cooperation.

We are the creators of a new fintech era!

Our mission is to revolutionize the world by making blockchain technology accessible to everyone in everyday life. WhiteBIT is a global team of more than 1,500 professionals united by a shared vision of shaping the future.

We are building our own blockchain ecosystem to ensure maximum transparency and security for over 8 million users worldwide. Our cutting-edge solutions, rapid adaptation to market challenges, and technological excellence set us apart from traditional companies.

Our official partners include Juventus, FC Barcelona, Lifecell, FACEIT, and VISA.

Join us as a Head of Data & Business Intelligence. 

Requirements:

- 8+ years of experience in Data Analytics, Business Intelligence, Management Reporting, Data Governance, or a related field.

- At least 3 years of experience leading a Data, BI, or Analytics team.

- Demonstrated experience building a Data/BI function from scratch or leading a substantial transformation of one; experience only maintaining a mature function is not sufficient for this mandate.

- Experience in an international, multi-entity, multi-business, or multi-project organization with complex stakeholder and reporting needs.

- Proven experience developing executive dashboards, management reporting, KPI architectures, metrics governance, and business-performance analysis.

- Strong understanding of financial and commercial metrics, including revenue, margin, contribution margin, CAC, LTV, churn, ARPU, conversion, and unit economics.

- Hands-on experience with Power BI, Tableau, Looker, or comparable BI platforms.

- Strong working knowledge of SQL, data modelling, semantic layers, data warehouses, data marts, and data-integration principles.

- Experience establishing data-quality controls, data catalogues, data ownership, and governance practices.

- Experience supporting forecasting, pricing, investment analysis, market-entry decisions, or scenario modelling is highly desirable.

- Ability to translate ambiguous business questions into scalable analytical solutions and communicate complex findings in clear business language.

- Strong systems thinking, commercial judgement, prioritization, stakeholder management, and influencing skills; confidence to challenge inconsistent assumptions and unsupported conclusions.

- Track record of building teams and capabilities in an environment of high ambiguity and evolving priorities.

- Bachelor’s degree in Data Analytics, Computer Science, Economics, Finance, Mathematics, Statistics, Business Administration, or a related field; relevant professional qualifications are an advantage.

Responsibilities:

- Build the Data & BI function from scratch: define its target operating model, team structure, roles, governance, processes, priorities, service model, and development roadmap.

- Recruit, lead, and develop the Data & BI team; manage capacity, performance, capability development, and delivery commitments.

- Create and maintain a Group-wide metrics framework and dictionary covering definitions, formulas, owners, official sources, refresh frequency, and approval status.

- Design the KPI architecture and KPI trees for the Group, businesses, projects, functions, and locations.

- Establish a single source of truth for management reporting and define the official systems, semantic models, and analytical data layers used for decision-making.

- Deliver scalable executive and management reporting, priority dashboards, and analytical solutions covering financial, commercial, growth, operational, location, and risk performance.

- Establish data-quality rules, monitoring routines, issue ownership, and escalation processes; coordinate resolution of inconsistencies with business and system owners.

- Reduce recurring manual and duplicated reporting through standardization, automation, and reusable analytical products.

- Translate strategic and operational business questions into clear analysis, scenario models, forecasts, and decision-ready recommendations.

- Define functional requirements for BI tools, data warehouses, data marts, semantic layers, and integrations in cooperation with technology teams.

- Enable responsible self-service analytics through standardized dashboards, documentation, training, access principles, and data-literacy initiatives.

- Develop practical standards for experiment measurement and ensure that analytical conclusions are supported by documented data and methodology.

- Prioritize analytical demand based on business value, urgency, data readiness, and available capacity; monitor adoption, reliability, and value of Data & BI products.

Working terms

Immerse yourself in Crypto & Web3:

• Master cutting-edge technologies and become an expert in the most innovative industry.

Work with the Fintech of the Future:

• Develop your skills in digital finance and shape the global market.

Take Your Professionalism to the Next Level:

• Gain unique experience and be part of global transformations.

Drive Innovations:

• Influence the industry and contribute to groundbreaking solutions.

Join a Strong Team:

• Collaborate with top experts worldwide and grow alongside the best.

Work-Life Balance & Well-being:

• Modern equipment.
• Comfortable working conditions, and an inspiring environment to help you thrive.
• 22 business days of paid leave.
• Additional days off for national holidays.
• Health insurance.

The product that needs your engagement:

Mobion & OnTaxi

Our mission is to propel the success of global ride-hailing companies by delivering intelligent, scalable SaaS solutions. Since 2016, we have optimized operations, enhanced user experience, and driven profitability with powerful analytics, intuitive interfaces, and flexible customization. With deep industry expertise and cutting-edge technology, we provide the agility and insights needed to thrive in any market, empowering businesses to adapt and grow in a fast-changing environment.

Technical stack: Python, Strong SQL, Kubeflow, MLflow, ETL.

Your future team of professionals:

You will be part of the Mobion product Data & Research team and work with highly motivated professionals who are passionate about the project. You will collaborate with engineers, product managers and analysts.

Your future challenges:

Design, launch and continuously improve ML-based dynamic pricing algorithms for a real-time marketplace.

Impact you will make:

— Development of machine learning models: Building and supporting models for pricing, demand forecasting, routing and analyzing customer behavior

— Data Science: Work with large volumes of data to uncover hidden dependencies and anomalies

— Deploying models to production: Collaborate with engineers to integrate models into the system

— Model monitoring and optimization: Constantly monitoring model latency, scalability, and implement versioning strategy

— Working with Business Teams: Collaborate with product managers and other teams to integrate models into the decision-making process

— A/B Testing and Model Evaluation: Analyze the results of experiments to improve the product

— Own the full lifecycle of ML solutions, from hypothesis and experimentation to production rollout and business impact measurement

Skills we are looking for:

— 4+ years of experience in data science

— Proven experience developing ML models for Surge Pricing, Demand Forecasting, or similar high-load, real-time prediction systems

— Experience working with time-series, geospatial data, and dynamic pricing algorithms is a strong plus

— Experience with Python (statistical and ML packages) and Spark

— Expert knowledge in SQL

— Knowledge of mathematical and applied statistics, probability theory, regression analysis

— Experience with ML tools: Kubeflow, MLflow, and ETL tools

— Experience in data preparation, feature engineering, and model evaluation.

— Git and Gitflow Workflow knowledge

— Successful experience in developing and implementing DS solutions into a product that led to improved business results

— English Upper-Intermediate or higher

Additional skills we would appreciate:

— Familiarity with mobility, logistics, or transportation data and KPIs (ETA predictions, surge pricing, driver utilization)

Benefits you get

Maintain your work-life balance

• Take control of your workday with our flexible schedule.
• 19 days of annual vacation granted on a pro-rata basis.
• No overtime required.

Hybrid/remote type of cooperation

Whether you prefer to work remotely in the comfort of your home office or from one of our 4 offices, you can help promote the global visibility of exceptional Ukrainian products from anywhere in the world.

Stay healthy

• Comprehensive medical insurance from a leading Ukrainian provider, including a wide range of services and special programs for relatives, and special options for those who live abroad.
• 15 working days of sick leave per year — because your health is our priority.

Grow with us

• In-house English courses to increase your proficiency through our online courses and speaking clubs with a native speaker.
• Online learning activities, including workshops, lectures, and webinars to enhance your leadership, management, and self-awareness skills.
• Experience exchange with our team of professionals who eagerly share their deep expertise across various fields.
• Opportunities for promotions, rotations, and transitions when you believe your skills could benefit a different role or team.

Stand with Ukraine!

We have an active pro-Ukrainian position! This means that we help our army, our servicemen, and their families not only through constant donations and volunteering but also through our military leave policy, special health insurance options, and financial assistance.

We are a perfect match if you share our values

We are professionals in our field.

We know how to turn up our professionalism to the maximum, because we are experts who enjoy solving complex tasks.

We know how to focus on the product, think big, and at the same time delve deep into the details.

We create a calm and friendly atmosphere within the company.

We value the freedom of open and transparent communications.

Radical honesty is embedded in the foundation of our culture.

We are open to new things and constantly develop and practice regular knowledge sharing, which helps us evolve continuously.

Most importantly, the company creates an environment where we can fulfill our potential upon a solid foundation.

Our Hiring process

• CV screening
• Test Task
• Recruiting interview
• Technical interview
• Offer call

We strive to ensure transparency and openness in the hiring process, and we understand the importance of providing timely feedback. If your resume meets the job requirements, we will contact you to clarify details and schedule an interview within 2 weeks after your application is submitted.
The timeframe for feedback between interview stages may take up to 2 weeks.

Interview process: Hr call 30min, 1 intro call + 1 technical interview (1 hour)
Location EU
Timezone: CET
English: C1 ideally
 

Critical Note
 This role is for an Architect, not a Data Engineer. Candidates who have only implemented pipelines without owning end-to-end architecture decisions will not be considered — this is explicitly called out multiple times by the client.
 

Project Overview
 Client needs a Data Architect to take ownership of an existing, complex, partially problematic Azure data platform — assess it quickly, separate tactical fixes from long-term architecture, and produce implementation-ready recommendations that engineering teams can act on immediately.
 

What You'll Do
Design, build, and optimize scalable data architectures on Databricks + Azure
Own end-to-end architecture decisions — not just implement pipelines
Assess an existing, incompletely documented platform and deliver concrete, actionable output within the first 1–2 weeks
Design scalable, reusable, metadata/configuration-driven ingestion frameworks (multiple databases, APIs, file-based sources)
Work hands-on with Azure Cosmos DB — data modeling, partition-key strategy, indexing, RU/throughput optimization, scaling, consistency, Change Feed
Work across Synapse workload patterns: Pipelines, Spark, Serverless SQL, Dedicated SQL Pools
Handle genuinely unstructured data — documents, PDFs, scans, free text, images, emails (real examples required, not theoretical)
Make technology-neutral architecture calls — comfortable concluding Databricks/Synapse/ADF may NOT be the right fit if scale/cost/requirements don't justify it
Separate and progress tactical stabilization vs. long-term target architecture in parallel
Produce clear architecture documentation, diagrams, and technical recommendations for engineering teams
Collaborate with engineering, analytics, and business stakeholders; mentor junior team members
 

Must-Have Requirements
Architecture ownership — proven, concrete examples of personally designing/owning a data platform architecture (not just pipeline implementation)
Azure — hands-on, recent (not years-old), 4+ years minimum. Azure DevOps usage alone does NOT count as Azure cloud experience
Databricks — must have real hands-on experience
Azure Cosmos DB — must have hands-on experience (scaling, partitioning, RU optimization, advanced design decisions) — this is one of the most heavily emphasized requirements in the entire brief
Azure Synapse — depth across multiple workload patterns, not surface-level exposure
Unstructured data — proven, real examples (not just structured/relational data experience)
Metadata/configuration-driven ingestion — must be able to explain a reusable ingestion framework design in depth
Existing platform modernization — concrete example of inheriting a problematic platform and improving it
Python, SQL, ETL/ELT
Strong data modeling (fact tables, dimensional/star schemas)
Batch + incremental processing/refresh
Strong communication with both technical and business stakeholders
CV must contain clear, detailed hands-on Azure experience — vague CVs will result in automatic rejection

Nice to Have
Future-oriented thinking on AI / natural-language querying of enterprise data
Experience with legislation/regulated data platforms (client referenced a similar past project: legislation data platform on Azure Synapse — XML/API pipelines, medallion architecture)
 

Interview Prep Note (for candidate)
 Client wants 2–3 strong real project examples structured as: Problem → options considered → personal decision → why → implementation → result. Expect deep technical probing on Cosmos DB and Synapse specifically, plus a scenario where Databricks is deliberately removed from the discussion to test technology-neutral thinking.

Our team is seeking a Data Solution Architect to further strengthen our capabilities.

Responsibilities

• Work closely with business in identifying solution requirements and key case-studies/scenarios to architect Data solution
• Participate in Data and Big Data initiatives on a company level
• Design Data analytics solutions by utilizing the Data technology stack with Big Data techniques
• Conduct solution architecture review/audit, calculate and present ROI
• Create and present solution architecture documents with deep technical details to customer and implementation teams
• Participate in specific “pre-sale” activities related to available experience and practice in order to prepare technical proposals on customer requests
• Lead implementation of the solutions from establishing project requirements and goals to solution "go-live"
• Maintain a strong understanding of technical solutions and architecture design trends and best practices, stay on cutting edge of Data technologies
• Constantly grow expertise by gathering and monitoring available EPAM project experience and ongoing projects with clients from different business domains to drive further EPAM business in Data field
• Create and follow personal education plan in the technology stack and solution architecture
• Share experience, knowledge and vision with EPAM, colleagues and customer teams. Participate in seminars, meet ups, mentoring, training programs. Prepare white papers and presentations

Requirements

• Strong ‘hands-on’ experience as a Data Architect with design/development background with Java, Scala, or Python
• Architecture experience and practice in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation and Security
• Experience with building traditional Cloud Data Warehouses, Data Lakes
• Knowledge of high load and IoT Data Platform architectures and infrastructures
• Wide experience in analysis, design, implementation, deployment as well as troubleshooting and rebuilding distributed Linux based platforms and Big Data solutions on premises and in Cloud
• Strong Cloud experience in at least one of the Cloud providers (AWS, Azure, GCP)
• Solid experience in continuous delivery tools and technologies
• Broad experience with Containers and Resource Management systems: Docker, Mesos, Kubernetes/OpenShift, Yarn
• Able to deliver Data Analytics projects and architecture guidelines
• Strong in research, comparison, and selection of tools / technologies / approaches to be used
• Practical experience in performance tuning and optimization, bottleneck problem analysis
• Strong communication skills, experienced in team coordination skills and solution implementation supervision
• Good in Agile development methodology, Scrum in particular
• Solid skills in business analysis, network/stack architecture, troubleshooting, support
• Fluent English

About the position

We are looking for a Middle Data Science / Computer Vision Engineer to join a team developing autonomous UAV capabilities for challenging operating environments, including scenarios with limited or unavailable GNSS and operator connectivity.

The role is focused on Computer Vision and Machine Learning for real-world autonomous systems. You will work on algorithms for optical navigation, object detection and tracking, and other perception tasks, with a strong emphasis on deployment to onboard computing platforms and validation in simulation, on the bench, and during flight tests.

We are looking for an engineer who is comfortable working beyond the model itself - analyzing system behavior, investigating test results, identifying root causes, and turning prototypes into reliable solutions that can operate on real UAV platforms.

Must have skills:

• Middle-level experience: approximately 2+ years of practical Data Science / Machine Learning experience with Computer Vision as the primary specialization
• Strong Python skills
• Hands-on experience with PyTorch and/or TensorFlow
• Hands-on OpenCV experience
• Good understanding of modern CNN- and Transformer-based CV architectures
• Practical experience in several of the following areas: object detection, object tracking, classification, segmentation, feature extraction/matching, image registration, motion estimation
• Understanding of Computer Vision geometry: camera models, coordinate systems, camera calibration, transformations, and projective geometry
• Good foundation in linear algebra, probability, and statistics
• Experience with Linux, Git, and sound software engineering practices
• Ability to work with imperfect real-world data collected from field systems and flight tests
• At least an Upper-Intermediate level of English (spoken and written)

Your tasks will include:

• Develop and improve Computer Vision algorithms for UAV applications
• Develop object detection, classification, and tracking algorithms
• Work on optical navigation, Visual Odometry / Visual-Inertial Odometry, feature matching, image registration, and visual localization
• Train, fine-tune, and evaluate models using proprietary datasets
• Build and optimize real-time CV pipelines
• Optimize inference for edge platforms with limited compute resources
• Integrate DS/CV components with navigation, flight controllers, telemetry, and guidance logic
• Participate in simulation, bench, and flight testing
• Analyze failed tests and algorithm degradation, and improve robustness

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

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)

We are looking for a Data Scientist to join our Trading Core and Risk Tech squads and drive data-informed decision-making across our trading systems. In a high-frequency trading environment processing billions in volume, success depends on precision, robust analytics, and the ability to turn complex data into actionable insights.

In this role, you will research, model, and validate the core data-driven models that drive our pricing engines, automated market-making algorithms, risk management frameworks (A/B/C-book optimization), and liquidation mechanics. You will sit at the intersection of statistics, data science, and high-performance software engineering, working directly with Core Product Managers and engineering teams to turn complex financial data into proprietary algorithmic advantages.

Responsibilities

• Research, design, and prototype behavioral, risk, and toxicity-scoring models for client and partner-flow segmentation
• Build backtesting and monitoring frameworks to validate models, signals, and hypotheses across data of varying granularity
• Detect early risk signals, anomalies, and regime shifts in market and client behavior, including probability of critical capital loss
• Develop explainable risk signals and labels for the R&D team, and long-term client value/risk models with forecasting
• Conduct research and hypothesis-testing on client economics, flow quality, and model performance

Requirements

• 4+ years of experience as a Data Scientist  
• Exceptional knowledge of probability theory, statistics, time-series analysis, and financial mathematics
• Advanced proficiency in Python (NumPy, Pandas, SciPy, Scikit-learn, Statsmodels) for data analysis, modeling, and backtesting
• Solid experience with Machine Learning
• SQL skills and experience working with large-scale historical market data (tick data, order logs)
• Strong logical thinking, initiative, and well-developed communication skills

Will be a plus

• Experience in CFD, Crypto CEX, Prop Trading Firm, or Hedge Fund
• Degree (MSc or PhD preferred) in a highly quantitative field: Mathematics, Physics, Statistics, Quantitative Finance, or Computer Science
• Deep understanding of market microstructure, order book dynamics, risk metrics (VaR, Expected Shortfall), and margin/liquidation mechanisms
• Experience with AI (Claude.io, Copilot, Codex)

We offer

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

Domain: Banking & Finance
Experience: 10+ years
Project Duration: September 1, 2026 – June 29, 2027
Format: Remote
Location: Poland

About the Project

We are looking for a Data & Machine Learning Architect to join a greenfield initiative focused on building a next-generation, cloud-native digital banking platform.

The project aims to create a scalable, modular, API-first, event-driven, and AI-powered ecosystem supporting real-time operations, faster product innovation, and sustainable business growth.

The platform will leverage modern Microsoft Azure services, advanced data technologies, and machine learning capabilities to enable digital transformation at scale.

Responsibilities

• Define and design end-to-end data and machine learning architectures using Microsoft Azure
• Lead the design and implementation of modern data platforms covering data lakes, data warehouses, real-time streaming, and analytics
• Develop scalable ML pipelines covering data ingestion, model training, deployment, monitoring, and automated retraining
• Establish MLOps practices, CI/CD standards, governance frameworks, and best practices across data and AI environments
• Ensure data quality, security, regulatory compliance, reliability, and operational excellence across the platform
• Collaborate with business and technical stakeholders to translate business requirements into robust and scalable technology solutions
• Provide architectural guidance, technical leadership, and mentorship to engineering teams
• Evaluate emerging technologies and contribute to the strategic roadmap for data and AI capabilities

Requirements

• 10+ years of professional experience across Data Engineering, Data Architecture, Analytics, Artificial Intelligence, or Machine Learning
• Proven experience designing and delivering enterprise-scale data and machine learning platforms within the Microsoft Azure ecosystem
• Advanced knowledge of Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage, Azure Machine Learning, AKS, and Azure DevOps
• Practical experience implementing MLOps practices, including ML lifecycle management, model governance, monitoring, and CI/CD automation
• Strong understanding of machine learning workflows, feature engineering, model deployment, and responsible AI principles
• Solid expertise in data governance, security, regulatory compliance, and metadata management
• Strong hands-on programming skills with Python and SQL
• Experience with containerization and orchestration technologies such as Docker and Kubernetes
• Strong leadership, communication, collaboration, and stakeholder management skills
• Fluent business and technical English

Tech Stack

• Data Engineering
• Data Analysis
• AI / Machine Learning
• Microsoft Azure
• Azure Data Factory
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Lake Storage
• Azure Machine Learning
• Azure DevOps
• CI/CD
• Python
• SQL
• Docker
• Kubernetes

Project Details

• Start date: September 2026
• Duration: 10 months
• Project type: Greenfield
• Verification process: Technical interview + project interview

ПРО НАС

UKRSIBBANK BNP Paribas Group — один з найбільших універсальних банків України. Ми об’єднуємо досвід та креативність у своїй команді, створюючи відкрите та інклюзивне середовище для розвитку кожного працівника.

Наші цінності — це відданість, інновації та відкритість, які допомагають нам досягати успіху в сфері банкінгу та робити позитивний вплив на суспільство.

Ми дякуємо нашим захисникам та захисницям, які віддано боронять свободу та незалежність України, та створюємо сприятливе середовище для роботи в банку.

З 2020 року UKRSIBBANK BNP Paribas Group проходить сертифікацію кращого роботодавця в Україні та Європі — Top Employer. Це єдиний банк в Україні, який має міжнародну сертифікацію Top Employers Institute.

Що ви будете робити на посаді :

• Моделювання та візуалізація даних середньої складності
• Розробка, тестування та моніторинг ML‑моделей (якість, стабільність, актуальність)
• Формування та перевірка гіпотез для покращення бізнес‑метрик
• Визначення вимог до даних, пошук джерел, збір та контроль якості (включно зі складними або відсутніми даними) з дотриманням комплаєнсу
• Розробка feature engineering (зокрема для часових рядів)
• Вибір та побудова моделей, оцінка якості, бізнес‑валідація результатів, документація
• Створення та тестування прототипів (A/B‑тести), оцінка бізнес‑ефекту
• Підтримка впровадження рішень для ІТ та бізнесу

Ми в пошуку в фахівця, який має:

• Повна вища освіта (магістр, спеціаліст)
• 2–4 роки в досвіду у Data Science / Machine Learning / Advanced Analytics / Applied AI
• Досвід роботи з Python, SQL
• Практичний досвід роботи з корпоративним аналізом даних, побудовою та оцінкою предиктивних та аналітичних моделей.
• Практичне розуміння сучасних підходів побудови прикладних AI рішень (ансамблів), зокрема на базі з LLM, OCR/VLM, RAG підходами буде суттєвою перевагою.
• Досвід роботи у банку або fintech буде перевагою.

Nice to have:

• досвід роботи Scala / Spark. Cloudera CML + H2O-3 (AutoML)
• досвід з Hive, Hadoop ecosystem або іншими корпоративними Data платформами
• практичний досвід або участь у проектах, пов’язаних з LLM / GenAI use cases, зокрема prompt engineering, RAG, evaluation pipelines, grounding, safety / guardrails та quality assessment (RAGAS)
• досвід роботи з OCR-рішеннями, включно з pre- / post-processing, classification / understanding, extraction, контролями quality
• досвід роботи з NMT, включно з оцінкою якості перекладу, доменною адаптацією та термінологічною узгодженістю
• досвід роботи з голосовими AI, зокрема STT / TTS
• досвід роботи з Azure AI Foundry

Окрім команди однодумців та цікавої роботи ви отримаєте:

Стабільність:

• Працевлаштування з дотриманням вимог чинного законодавства України
• своєчасна виплата заробітної плати
• програми медичного страхування та страхування життя
• 25 днів щорічної відпустки, додаткові дні відпочинку на пам’ятні події, соціальні відпустки у відповідності до законодавства України
• щорічні перегляди заробітної плати відповідно до персональної ефективності та фінансових показників банку
• встановлення строку випробування відповідно до вимог чинного законодавства

Розвиток своїх талантів заради кар’єри:

• можливість навчання: Школа лідера, Сервіс дизайну, Бізнес аналітики, Data, Digital, Agile та програму розвитку талантів I-Players та широкий набір мікро-тренінгів (SQL, BI, EQ, тощо).
• можливість брати участь у програмі внутрішньої та міжнародної мобільності до BNP Paribas Group
• підтримку працівників постійно навчатись та професійно розвиватись. Щороку наші працівники складають індивідуальний план розвитку разом з керівником чи ментором і впевнено рухаються до мети

Краще місце для роботи:

• Робота з періодичною можливістю працювати дистанційно (для вакансій з дистанційним форматом роботи)
• програму «War&Life balance: як повернути життя в життя» — це практичні воркшопи з фахівцями для підтримки емоційного стану
• в рамках програми «New Ways of Working» дайджест з порадами від експертів щодо підтримки фізичного та ментального здоров’я
• різноманітність, інклюзивність
• залучення до проєктів сталого розвитку та корпоративно-соціальної відповідальності

Бажаєш дізнатися більше? Додаткова інформація може бути надана на наступних етапах розгляду вакансії.

#veteranfriendly

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