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Satori Analytics is a fast-growing scale-up of 100+ tech specialists delivering innovative data and AI solutions across industries including FMCG, retail, manufacturing, and financial services. The company operates cloud-based ecosystems and predictive models serving global brands across the data lifecycle.
You will join the Data Science team to drive customer and marketing analytics projects. Your primary focus will be building segmentation and targeting solutions using customer, transactional, campaign, and behavioral data. You'll partner closely with Marketing, BI, and Data Engineering teams to translate commercial questions into actionable recommendations.
Key responsibilities include: designing customer segmentation solutions using clustering techniques (K-Means, Gaussian Mixture Models, DBSCAN); engineering customer-level features such as recency, frequency, monetary value, spend trends, and lifecycle indicators; applying explainability techniques (particularly SHAP) to understand model behavior and translate insights into customer narratives and personas; contributing to targeting, campaign analytics, propensity modeling, and churn prediction; defining meaningful KPIs with Marketing and BI; presenting findings to technical and non-technical stakeholders; and writing clean, reusable, well-documented code in collaboration with Data Engineers.
Required experience includes professional background in Data Science, Customer/Marketing Analytics, or Business Analytics with a track record partnering with Marketing or CRM teams. You should have hands-on experience with customer segmentation, clustering, behavioral analytics, and targeting projects, with solid understanding of clustering algorithms. Strong applied statistics knowledge (distributions, regression, hypothesis testing, experimentation) and familiarity with customer/marketing KPIs (engagement, conversion, retention, churn, customer value) are essential. Technical skills must include Python or R, solid SQL (joins, aggregations, CTEs, window functions), and data visualization/BI principles. You should be able to translate business questions into analytical problems and communicate findings clearly to non-technical audiences, with strong documentation habits and Git experience.
Bonus qualifications include CRM analytics, loyalty programs, media analytics, customer lifecycle management, propensity modeling, recommendation systems, customer lifetime value, uplift modeling, A/B testing, experiment design, causal inference, experience with payment/banking/retail/FMCG data, BI tools (Power BI, Tableau), and cloud platforms (Azure, AWS, GCP, Microsoft Fabric, Databricks).
The role offers a competitive salary, hybrid work model with flexibility to work remotely from anywhere in the European Economic Area or UK (up to 6 weeks per year), training budget for certifications and courses from top tech partners, private insurance, and top-tier tech equipment.
