Data Scientist (Applied Analytics)

At Mozzart, people make the difference. What sets us apart is a culture built on trust, shared knowledge, and space for ideas to grow. Operating across seven markets in Europe and Africa, we are committed to creating a workplace where people feel supported, valued, and motivated to develop. Our success is grounded in expertise, continuous learning, and a responsible approach to business. Recognised as a Top Employer and an Oscar of Quality award winner, we remain focused on what truly matters - collaboration, personal growth, and long-term impact. Beyond our teams, we stand by the communities we are part of, supporting initiatives in sports, education, healthcare, and humanitarian causes. Who you play with matters.

We are looking for a Data Scientist to work on applied analytics and practical ML models in service of the business. The focus of this role is independent work in SQL and Python on data preparation, user segmentation, campaign analysis, analysis of products and benefits offered to users, scoring models, and other predictive solutions, in close collaboration with Data Analysts. This is not a research role — we want someone who can turn data into solutions used in campaigns, CRM, and performance tracking.

 

• Prepare datasets from the DWH (SQL) and develop features for segmentation and predictive models.
• Build and validate practical ML models (e.g. churn, propensity, campaign scoring, classification / regression) with clear business interpretation of results.
• User segmentation and support for campaign and ROI analysis through scores, segments, and effect measurement, together with Data Analysts.
• Analyse products and benefits offered to users — what works better for retention, engagement and monetisation.
• Monitor model quality and usefulness in real business processes.
• Collaborate with the team on data quality, reproducibility, and inputs for business presentations and insights.

 

• Basic to intermediate SQL (joins, aggregations, data cleaning, quality checks) and understanding of DWH work.
• Basic to intermediate Python (Pandas; Scikit-Learn, XGBoost, or similar modelling libraries are a plus).
• Understanding of how models and segments are used in the business (campaigns, CRM, KPI tracking), not only offline evaluation.
• Advantage: B2C industry experience (banking, insurance, telco, e-commerce) and/or work on churn / scoring / segmentation / campaign and product analysis.
• Advantage: experience running scripts and models beyond a local machine only (e.g. server environment, shared repository / Git).

Your work-life balance is essential to us, so we offer you:

• 22 - 26 days of annual leave
• 38-hour working week, because we value your time
• Flexible working hours
• Hybrid working model

 

Your health and well-being is crucial to us, so we have you covered:

• Private health insurance
• Mental health and well-being initiatives
• Open feedback culture

 

We care about your personal development and professional growth, so we provided:

• Career development program
• Opportunity to take technical, language and soft skills trainings