Data Scientist (Machine Learning)

Quick Facts

• Role: Data Scientist (Machine Learning)

Description

Build and optimize predictive machine learning models (e.g., churn, propensity, segmentation, CLV, recommendations) using consumer and marketing data. Analyze customer and marketing data from multiple sources, model customer journeys, and translate results into actionable business recommendations. Present insights to non-technical stakeholders and monitor model performance to measure impact on marketing KPIs and P&L.

Responsibilities

• Build and optimize predictive models (churn, propensity, segmentation, CLV, recommendations)

• Analyze consumer and marketing data across multiple sources

• Model and optimize customer journeys using AI/ML techniques

• Collaborate with marketing and product teams to define analytical priorities

• Translate complex findings into clear business recommendations

• Provide analytics outputs with guidance for business teams

• Create high-quality presentations, reports, and data visualizations for non-technical stakeholders

• Track model performance and measure business impact on marketing KPIs and P&L

• Identify opportunities for data-driven growth and promote data-based decision-making

Requirements

• Minimum 5 years of experience as a Data Scientist

• Strong proficiency in SQL (complex queries, joins across large datasets, data preparation for modeling)

• Proficiency in Python (pandas, numpy, scikit-learn, statsmodels or similar) for analysis, modeling, and result validation

• Experience with large datasets and ETL processes

• Ability to interpret analytical results in a business context

• Commitment to code quality and reproducibility of analyses

• Effective English communication in an international environment

Benefits

• Private healthcare

• Benefits cafeteria platform

• Car discounts

• Comfortable workplace (class A offices or remote work)

• Profit sharing with workers

• Investment in growth (meetups, webinars, training platform, technology blog)

• Budget for ideas and voluntary actions

• Opportunities across many projects for global brands