Senior Data Scientist
TechTree
⚲ Warszawa
160 - 170 PLN/h netto (B2B)
Wymagania
- Machine Learning
- SQL
- Python
- Cloud Computing (Databricks, GCP, Azure)
- Data Science
Opis stanowiska
ABOUT THE COMPANY Our client is an end-to-end data services partner to global enterprises, founded in 2008 and headquartered in Warsaw. Our teams work with over 75 leading consumer packaged goods brands across more than 30 countries, helping them unlock the full value of their data — from strategy and development through to operations and adoption. Our work spans supply chain analytics, customer analytics, AI and machine learning, data platforms, and digital commerce. We are recognised as a Strong Performer in the Gartner Peer Insights Voice of the Customer report for data and analytics, and hold Great Place to Work certification in multiple countries. ABOUT THE ROLE Our Data Science and AI team delivers machine learning solutions for global clients, with a particular focus on forecasting, customer analytics, and causality frameworks. Projects span next best offer and action modelling, propensity and churn modelling, demand and sales forecasting, and revenue growth management. As a Senior Data Scientist, you will own end-to-end delivery across classification and forecasting use cases, bringing strong technical depth and the confidence to operate independently on complex problems. You will work closely with business stakeholders and cross-functional engineering teams, and be expected to translate business problems into well-scoped machine learning solutions. The role also involves pre-sales activity and direct client engagement at a senior level. WHAT YOU'LL WORK ON End-to-end modelling Own classification and forecasting use cases from problem framing through data preparation, feature engineering, model training, and evaluation — covering demand forecasting, churn prediction, and similar applications. Data exploration and quality Perform exploratory data analysis on tabular and time-series data, identify quality issues early, and engineer features that feed robust production models. Model development and validation Train, tune, and validate ML models — logistic regression, tree-based models, gradient boosting, simple neural networks, and classical time-series models — with evaluation frameworks clearly tied to business KPIs. Stakeholder communication Build clear visualisations and concise reports to present model results and insights to business stakeholders. Lead requirements gathering, define success metrics, and manage expectations confidently at a senior level. Production collaboration Work with data engineers and AI engineers to bring models into production — batch scoring, APIs, model monitoring, and dashboards — ensuring clean, well-documented handoffs. Documentation and reproducibility Document data sources, modelling assumptions, and experiment results across notebooks, reports, and wikis to a standard others can build on. Pre-sales Contribute to pre-sales activities including scoping, estimation, and solution design for prospective clients. WHAT WE LOOK FOR Strong classical data science and ML background Solid commercial experience across the full ML workflow, with a track record of independently delivering production systems that drive measurable business impact. Customer analytics or advanced forecasting expertise Hands-on experience in customer analytics (propensity, churn, next best action) or advanced forecasting (demand, sales). Familiarity with causality frameworks is a strong advantage. Hyperparameter tuning and validation frameworks Solid knowledge of model tuning approaches and validation frameworks, with a clear understanding of how metric choices connect to business outcomes. Business requirements and technical planning Experience gathering requirements from non-technical stakeholders, defining success metrics, assessing data feasibility, and translating ambiguous problems into concrete technical plans. Python and SQL Fluent in Python for data science and modelling work. Solid working knowledge of SQL for data access and exploration. THE TEAM You'll join a specialist Data Science and AI practice working alongside experienced consultants, ML engineers, and data engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates. COMPENSATION & BENEFITS Rate 160 – 170 PLN per hour on a B2B contract, depending on experience. Contract flexibility Flexibility on working hours and preferred form of contract. Workation policy Option to work remotely from other locations for defined periods. Onboarding Comprehensive online onboarding programme with a dedicated buddy from day one. Learning and development Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year. Career growth Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation. Referral bonuses Financial rewards for successful employee referrals. Wellbeing Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives. Equipment Modern office equipment provided. Employer recognition Great Place to Work certified employer.