Data Scientist

About the Project

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We are looking for a Data Scientist to join a product analytics team working on retention, growth, pricing, and customer behaviour for a subscription-based SaaS product. The role combines deep analytical work, experimentation, predictive modelling, and clear communication with product and business teams.

The technical environment includes Python, SQL, BigQuery or Snowflake, Jupyter, statistical analysis, dashboarding tools, and collaboration with data engineering for production-ready datasets. The role requires strong spoken English for presenting findings, challenging assumptions, and aligning recommendations with international stakeholders.

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What You Will Do

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• Analyse user behaviour, retention, conversion, churn, pricing impact, and product adoption patterns.
• Build analytical datasets, cohorts, funnels, segmentation models, and clear business-facing insights.
• Design and evaluate experiments, A/B tests, and quasi-experimental analyses where applicable.
• Develop predictive models for churn, lead scoring, customer value, or usage-based segmentation.
• Create dashboards and recurring reports that help product and leadership teams make decisions.
• Work with product managers to define metrics, success criteria, and measurement plans.
• Explain analytical results in a practical way, including uncertainty, limitations, and recommended next steps.

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What We Are Looking For

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• 3+ years of commercial experience in data science, product analytics, or applied analytics.
• Strong SQL skills and experience working with large analytical datasets.
• Strong Python skills with Pandas, NumPy, scikit-learn, statsmodels, or similar tools.
• ‍Good understanding of statistics, experimentation, model evaluation, and business metrics.
• Experience with BI/dashboarding tools such as Looker, Tableau, Power BI, or Looker Studio.
• Ability to translate ambiguous business questions into structured analysis.
• Strong spoken English - B2+ or higher for presenting insights to international product and business stakeholders.

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Nice to Have

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• Experience with subscription analytics, churn modelling, pricing analysis, or growth analytics.
• Experience with BigQuery, Snowflake, dbt, or modern data warehouses.
• Experience with causal inference, uplift modelling, or experimentation platforms.
• Experience working closely with product teams in SaaS, fintech, marketplace, or e-commerce domains.

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Apply

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If you enjoy turning complex data into product and business decisions, we would be glad to hear from you. Send us your CV and we will contact you to discuss relevant opportunities.

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