Lead Data Scientist

We are looking for a Lead Data Scientist to lead the delivery of business-focused Machine Learning and Data Science solutions, with a strong emphasis on Forecasting and Customer Analytics. This is a senior, client-facing role that combines hands-on modeling expertise with leadership in end-to-end project execution. You will collaborate closely with stakeholders to translate complex business challenges into structured ML solutions and guide projects from framing through deployment support.

This is a fully remote role for candidates based in Poland.

Role Details

Location: Remote (Poland)

Employment Type: Full-time (Permanent – UoP or B2B)

Seniority Level: Lead

Start Date: ASAP

Offices are located in Warsaw and Lublin, but the role is fully remote.

Mission & Context

The team delivers business solutions using Machine Learning and Data Science, often transforming them into scalable platforms. Projects focus on Forecasting and Customer Analytics, leveraging classical ML models and advanced causal frameworks.

Example domains include:

• Next Best Offer / Next Best Action
• Propensity modeling
• Churn prediction
• Demand and sales forecasting
• Revenue growth management
  

This role has been created to lead end-to-end delivery — from stakeholder collaboration and business problem framing to model development, validation, and deployment support. The culture strongly values diversity, equity, and inclusion.

Key Responsibilities

• Lead end-to-end classification and forecasting use cases
• Frame business problems and define success metrics
• Perform data exploration (EDA), cleaning, and feature engineering
• Train, validate, and tune ML models (logistic regression, tree-based models, gradient boosting, neural networks, classical time-series models)
• Apply hyperparameter tuning and validation frameworks
• Evaluate models using business-relevant KPIs
• Build clear visualizations and concise stakeholder reports
• Collaborate with data and AI engineers on productionization (batch scoring, APIs, monitoring, dashboards)
• Document modeling assumptions, experiments, and data sources in a reproducible manner
• Align stakeholder expectations and audit data feasibility
• Participate in pre-sales activities at senior level
  

Required Skills

• Strong commercial experience with classical Data Science and ML models
• Solid expertise in Customer Analytics or Advanced Forecasting
• Experience with hyperparameter tuning and validation frameworks
• Proven ability to gather business requirements and translate them into technical plans
• Fluency in Python
• Working knowledge of SQL
• Experience with Cloud platforms (Databricks, GCP, Azure)
• Strong stakeholder communication skills
  

Candidate Profile

• Has deep, hands-on ML experience in business applications
• Demonstrates strong commercial awareness and client-facing capability
• Understands how model performance translates into business value
• Can independently define technical roadmaps for analytics initiatives
• Is comfortable leading discussions with non-technical stakeholders
• Operates with ownership and structured thinking
• The company is also open to strong mid-level and exceptional junior candidates if they demonstrate high potential.