Lead/Senior Data Scientist (ML)

TL;DR

Lead/Senior Data Scientist (ML): Work on end-to-end classification and forecasting use cases including demand forecasting, churn prediction, and customer analytics with an accent on feature engineering, model development, and business impact evaluation. Focus on translating business problems into ML solutions, collaborating with stakeholders and engineers for production deployment, and presenting insights through visualizations and reports.

Poland

Company

Established data science and ML consulting firm delivering scalable platforms for forecasting and customer analytics across global sites.

What you will do

• Handle end-to-end ML workflows for classification and forecasting: problem framing, data prep, modeling, evaluation, and deployment support.
• Perform EDA, data cleaning, and feature engineering for tabular and time-series data.
• Train, tune, and validate standard ML models like gradient boosting, logistic regression, and time-series models.
• Evaluate models against business KPIs and create visualizations/reports for stakeholders.
• Collaborate with data engineers and AI engineers for productionizing models via APIs, monitoring, and dashboards.
• Document work reproducibly and engage in business understanding, pre-sales at senior level.

Requirements

• Commercial experience with classical ML models (decision trees, ensembles, linear regression).
• Solid knowledge of customer analytics or advanced forecasting.
• Model hyperparameter tuning and validation frameworks.
• Experience gathering business requirements, data processing, feature engineering, and model evaluation.
• Fluency in Python, basic SQL, and DS/ML libraries.
• Experience with Databricks, GCP, or Azure.

Nice to have

• Understanding of causal machine learning.
• Big data and distributed environments.
• Multiple forecasting projects.
• OOP in Python, MLOps, R, or Scala.

Culture & Benefits

• Stable employment with flexibility in hours and contract forms.
• Workation policy for inspiring locations.
• Comprehensive onboarding, Udemy access, certificate programs, and upskilling support.
• Diverse inclusive community, internal promotions, autonomy, and well-being activities.
• Modern office equipment and charity/environmental opportunities.