Data Scientist

• Responsible for designing of solutions’ architecture for organization in a cloud, together with driving your teams success.
• Use the most advanced technology stack and have an opportunity to implement new solutions while working with top leaders in their industries.
• Driving growth of your direct team and assuring its soft-skills and technical expertise development.
• Solving complex business problems at large scale.
• Participating in a cross-functional initiatives and collaborating across various domains.
• Interacting with specialists, product/project managers and partners from all over the world.

AI & Data Manager

• Drive the strategic vision for AI/ML initiatives and contribute to the overall AI strategy of the company
• Communicate complex technical concepts and results to business stakeholders effectively
• Provide thought leadership and subject matter expertise in data science
• Collaborate with cross-functional teams to understand business needs and translate them into data science solutions
• Lead a team of data scientists, MLOps, ML engineers, solution architects providing guidance, mentorship, and coaching
• Oversee the end-to-end lifecycle of multiple AI/ML projects, from data collection and preprocessing to model training, evaluation, and deployment
• Leverage Agentic AI, generative AI and large language models (LLMs) to create innovative applications and solutions
• Design, Develop and implement data science projects, including machine learning models, deep learning models, Agentics and Generative AI, NLP solutions, statistical analysis, and data visualization
• Ensure data quality, scalability and reliability of AI systems
• Stay up to date with the latest data science trends and technologies
• Contribute to the development of data-driven solutions and products
• Present data science generated insights and recommendations to stakeholders

Data Scientist Lead

• Understand end-to-end business problems, analyze relevant data and identify high-value opportunities where Data Science, generative AI and agentic workflows can improve efficiency, quality and customer experience
• Assess use cases regarding business value, data availability, statistical feasibility, operational impact, implementation effort and alignment with the bank’s strategic objectives
• Design and implement AI-supported agents, data-driven automation solutions and LLM-supported workflows using suitable software development practices
• Collaborate with Product Owner, architects, developers and business stakeholders to ensure that implemented solutions are production-oriented, maintainable and aligned with banking requirements

Business Expert – Data Scientist

• Developing credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections
• Design and run experiments to optimise approval rates, loss rates, and profitability
• Partner with product squads to embed decision logic into real-time systems
• Ensure data quality, compliance, and ethical use of models across all decisioning processes
• Mentor product squads on best practices in experimentation and data-driven decision making
• Provide models to optimise outcomes in collections, churn management and user retention

Data Science Manager – Credit

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Senior Data Scientist

• Lead a small clinical study or co-lead a larger study or studies with moderate guidance.
• Be able to support several clinical studies with minimal guidance.
• Manage and monitor the progress of data management activities with CROs or other vendors on assigned studies.
• Review protocols for appropriate data capture including electronic Case Report Form (eCRF) design.
• Be able to perform a thoroughly detailed review of eCRF data requirements.
• Interact with CRAs, programmers, study managers and statisticians in designing eCRFs and creating the annotated eCRF and CRF completion guidelines.
• Develop data edit check specifications and run data listings as required.
• Coordinate the design and testing of Electronic Data Capture (EDC) systems according to company standards.
• Able to resolve EDC system issues with team members.
• Develop the Data Management Plan for a clinical study.
• Able to review and provide feedback to the clinical team on other study documents e.g. Clinical Monitoring plans, Statistical analysis plans and vendor specifications.
• Enter data queries into the EDC system to be resolved at investigational sites and manage the resolution of those queries.
• Perform reconciliation of header data from external data sources against the clinical database.
• Perform Serious Adverse Event reconciliation activities according to SOPs and guidelines.
• Assist in database upgrades/migrations including performing User Acceptance Testing.
• Able to maintain study workbooks and data management files.
• Perform database lock and freeze activities per company SOPs.
• Participate in regular team meetings and provide input when appropriate.
• Provide input into the development of data management SOPs, Work Instructions, and process documents.
• Assist with the training of new employees and/or contractors.
• Collaborates with cross-functional teams to design and implement effective data collection strategies, ensuring high-quality data capture and timely resolution of data queries throughout the clinical trial lifecycle.

Clinical Data Manager – FSP

• Lead negotiations with suppliers on a portfolio of strategic and complex External Data projects
• Act as a trusted business advisor to EY stakeholders
• Work closely with key internal teams to minimize risk to the organization
• Provide accurate progress reporting on all projects
• Identify and leverage digital tools, procurement technologies, and artificial intelligence (AI) solutions
• Use tools to perform supplier and market research
• Employ procurement and category best practices to projects
• Interact with procurement specialists and business stakeholders across multiple locations
• Work closely with other business partners and manage all aspects of the contracting process
• Drive awareness of the procurement process with local EY staff and stakeholders as needed

Sourcing Manager

• Own and extend our offline eval suite across products — datasets (capability + regression), judges, metrics
• Build and maintain online quality dashboards: resolution rate, CSAT, thumbs up/down, LLM-as-judge signals, error rate, latency
• Close the production feedback loop: mine failure patterns from real traffic → turn them into regression cases → propose fixes to Product and domain experts
• Harden methodology: judge stability, non-determinism handling
• Translate numbers into decisions – weekly syncs, clear trade-offs, no dashboards for their own sake

Product Data Scientist – AI Evaluation, Quality

• Lead the design, implementation, and deployment of ML/DL algorithms.
• Apply quantitative analysis and an insightful presentation of data to see beyond the numbers and understand how our users interact with our growth product.
• Apply data mining techniques, perform statistical analysis, and build high-quality predictive models.
• Meet the business vision and strategy in accordance with the product innovation backlog.
• Collaborate with the product and engineering teams to deliver usable and informative analytical interfaces.

• Tworzenie i rozwój modeli analitycznych dla obszarów: process mining, churn analysis, fraud prevention, NLP
• Identyfikowanie, pozyskiwanie i przygotowanie danych — zarówno wewnętrznych, jak i zewnętrznych
• Ścisłą współpracę z interesariuszami biznesowymi: zbieranie wymagań, budowanie wizji produktu, angażowanie partnerów w realizację projektu
• Wdrażanie gotowych rozwiązań i współtworzenie strategii rozwoju produktów analitycznych
• Promowanie podejścia „T-shaped Data Scientist” – łączenia głębokiej wiedzy eksperckiej z szerokim spojrzeniem produktowym i inżynierskim

• Partner with our Product and Business Teams to understand their needs, translate them into data science solutions, and provide actionable insights.
• Develop and implement data science solutions (ML models, GenAI products, hybrid approaches, data analytics) to optimize marketing and products strategies, enhance user experience and shape targeting.
• Collaborate closely with cross-functional teams (e.g. other Data&AI teams, Technology teams) to ensure seamless integration of data-driven initiatives.
• Stay ahead of the curve exploring cutting-edge methods and being on top of new trends in Data Science & AI.
• Communicate insights and recommendations to the management and business teams, and other data community members.

Senior Data Scientist – Personalisation

• Run end-to-end forecasting analyses on real business problems
• Build and evaluate time series and machine learning forecasting models
• Write clean, well-structured code and take part in code reviews
• Take ownership of your tasks: estimate your work, communicate progress, and flag issues early to deliver on time
• Support the full lifecycle of our forecasting products
• Keep learning - deepening your technical foundations and forecasting expertise

Junior Data Scientist

• Drive advanced analytics, causal reasoning, and AI-powered decision intelligence across multiple use cases
• Build production-grade systems that combine predictive, causal, and generative AI capabilities
• Turn complex data into actionable insights, automated decisions, and intelligent workflows
• Design and deploy systems that integrate experimentation, observational data, machine learning, and generative AI
• Collaborate closely with data engineers, ML engineers, analysts, and platform teams

• Partner with Product and BI to turn business goals into well-scoped ML problems with clear success criteria and guardrails
• Build and productionize models for segmentation, churn, LTV, and recommendations
• Design evaluation frameworks including offline benchmarks and online feedback loops to ensure models are measured, not assumed
• Collaborate with Engineering on production design considerations like latency, payload structure, fallbacks, and failure modes
• Monitor model performance over time, detect drift, and own retraining and iteration cycles
• Use product telemetry and user feedback to drive continuous model and feature improvements
• Work alongside AI coding agents to accelerate development (pipelines, tests, refactoring, exploration) while maintaining human oversight
• Communicate results, trade-offs, and recommendations clearly across technical and non-technical teams

• Responsible and manages all aspects of the clinical trial data management process
• Ensure that clinical data management deadlines are met with quality
• Oversee project data entry process including development of data entry guidelines
• Conduct database build UAT and maintain quality controlled database build documentation
• Perform quality control of data entry
• Train clinical research personnel on the study specific CRF
• Review and query clinical trial data according to the Data Management Plan
• Liaise with third-party vendors such as external data and EDC vendors in a project manager capacity
• Identify and troubleshoot operational problems and issues
• Participate in the development and maintenance of Standard Operating Procedures (SOPs)

Clinical Data Manager II/Senior Clinical Data Manager

• Primary Data Management (DM) contact (Lead DM role) for assigned clinical project(s) / program(s), ensuring that there is back-up, continuity, responsiveness, and that tasks are performed in a timely manner. May support another Lead DM as a back-up and/or team member. May include DM oversight of sponsor programs.
• Oversee project data entry process including development of data entry guidelines, training, data entry quality and resourcing
• May perform quality control of data entry
• Provide input, assesses and manage timelines. Ensure that clinical data management deadlines are met with quality. Assess resource needs for assigned projects, as needed.
• May develop CRF specifications from the clinical study protocol and coordinate the review/feedback from all stakeholders
• Conduct database build UAT and maintain quality controlled database build documentation. Oversee overall quality of the clinical database.
• May specify requirements for all edit check types e.g. electronic, manual data review, edit checks, etc. Oversee development of the edit check specifications and manual data review specifications
• Responsible for creating, revising, appropriate versioning and maintaining data management documentation. Oversee completeness of data management documentation for the Trial Master File.
• Train clinical research personnel on the study specific CRF, EDC, and other project related items as needed.
• Review and query clinical trial data according to the Data Management Plan
• Perform line listing data review based on the guidance provided by the sponsor and/or Lead DM
• Run patient and study level status and metric reporting
• Perform medical coding of medical terms relative to each other in order to ensure medical logic and consistency
• Coordinate SAE/AE reconciliation
• Liaises with third-party vendors such as external data and EDC vendors in a project manager capacity in support of timelines and data-related deliverables
• May assist with SAS programming and quality control of SAS programs used in the Data Management department
• Identify and troubleshoot operational problems, issues, obstacles, and barriers for studies based on metrics data, audit reports, and input from project team members and other stakeholders
• May assist in reviewing and providing feedback on protocols, Statistical Analysis Plans (SAP) and Clinical Study Reports (CSRs), if required by the project
• Participate in the development and maintenance of Standard Operating Procedures (SOPs) and corresponding process documentation related to data management and database management activities
• May attend strategy meetings, bid defense prep meetings, bid defenses, capability presentations, potential client engagement meetings
• May review Request for Proposals (RFP), proposals, provide project estimates
• Provide leadership for cross-functional and organization-wide initiatives, where applicable
• Trains and ensures that all data management project team members have been sufficiently trained
• Communicate with study sponsors, vendors and project teams as needed regarding data, database or other relevant project issues
• May present software demonstrations/trainings, department/company training sessions, present at project meetings
• May require some travel
• Perform other duties as assigned

Clinical Data Manager II / Senior Clinical Data Manager

• Design, develop, and deploy machine learning and AI-enabled solutions that support partnering activities such as opportunity prioritization, portfolio intelligence, forecasting, operational insights, and decision support.
• Apply advanced analytics, statistical modeling, machine learning, and emerging AI techniques to solve complex business problems and deliver scalable intelligence capabilities across the partnering ecosystem.
• Lead exploratory data analysis, feature engineering, model selection, training, validation, and performance evaluation for machine learning and AI-enabled solutions.
• Partner closely with business stakeholders and product teams to translate complex business challenges into analytical approaches, machine learning solutions, and scalable intelligence capabilities.
• Collaborate with AI, data, and engineering teams to operationalize AI-enabled capabilities and support the adoption of scalable intelligence solutions across partnering platforms and workflows.
• Design and develop analytics solutions, dashboards, KPIs, and intelligence capabilities that improve visibility into partnering operations, opportunities, and portfolio activities.
• Collaborate with engineering and architecture teams to support operationalization of machine learning and AI-enabled solutions in production environments.
• Communicate analytical findings, model outputs, and AI-driven insights through clear visualizations, presentations, and storytelling.

Data Scientist jobs in Poland

See all jobs on JobTailor

AI & Data Manager

Data Scientist Lead

Business Expert – Data Scientist

Data Science Manager – Credit

Senior Data Scientist

Clinical Data Manager – FSP

Sourcing Manager

Product Data Scientist – AI Evaluation, Quality

Data Scientist

Data Scientist

Senior Data Scientist – Personalisation

Junior Data Scientist

Senior Data Scientist

Data Scientist

Clinical Data Manager II/Senior Clinical Data Manager

Clinical Data Manager II / Senior Clinical Data Manager

Data Scientist – Applied AI