Clarity in decision making through Data and AI.
Data Scientist – Customer & Marketing Analytics
Location
Greece
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Data Scientist – Customer & Marketing Analytics
Satori Analytics
**What Your Day Might Look Like:** - **Segment the customers:** Design segmentation solutions from customer, transactional, and behavioural data using clustering techniques such as K-Means, Gaussian Mixture Models, or DBSCAN. - **Engineer the signal:** Build customer-level features — recency, frequency, monetary value, spend trends, engagement, and lifecycle indicators — and evaluate results through metrics, stability analysis, and business interpretability. - **Explain the "why":** Use explainability techniques, particularly SHAP, to understand model behaviour and translate feature importance into clear customer narratives, profiles, and personas. - **Go beyond segments:** Contribute to targeting, campaign analytics, propensity modelling, churn prediction, and other marketing use cases, surfacing patterns and performance drivers in customer and marketing KPIs. - **Align with the business:** Work with Marketing and BI to define meaningful KPIs and connect analytical outputs to business objectives. - **Tell the story:** Present findings to technical and non-technical stakeholders through clear visualisations and business language. - **Work clean:** Write reusable, reproducible, well-documented code, collaborating with Data Engineers and BI to prepare and validate datasets.
Job Requirements
- Your Superpowers 🚀:**
- Professional experience in Data Science, Customer/Marketing Analytics, Business Analytics, or a related field, with a track record partnering with Marketing, CRM, or other business-facing teams.
- Hands-on experience with customer segmentation, clustering, behavioural analytics, or targeting projects — including a solid grasp of clustering algorithms, their assumptions, strengths, and limitations.
- Comfort evaluating clustering solutions through metrics, stability testing, distribution analysis, and business interpretability.
- Experience with explainable AI, particularly SHAP, and the ability to turn explainability outputs into meaningful business insight.
- Good grounding in applied statistics (distributions, regression, hypothesis testing, experimentation, model evaluation) and a good understanding of customer and marketing KPIs (engagement, conversion, retention, churn, customer value).
- Strong Python or R and solid SQL (joins, aggregations, CTEs, window functions), plus familiarity with data visualisation and BI principles.
- Ability to translate business questions into structured analytical problems and communicate findings clearly to non-technical audiences.
- Strong documentation habits, experience with Git, and the ability to work independently and flag risks proactively.
- Bonus Points for:**
- CRM analytics, loyalty programmes, media analytics, or customer lifecycle management.
- Propensity modelling, recommendation systems, customer lifetime value, uplift modelling, or next-best-action solutions.
- A/B testing, experiment design, causal inference, or campaign incrementality.
- Experience with payment, banking, retail, FMCG, or large-scale transaction data, and BI tools like Power BI or Tableau.
- Cloud and analytics platforms (Azure, AWS, GCP, Microsoft Fabric, Databricks), distributed processing (Spark, PySpark, Dask), and exposure to MLOps or Generative AI / LLM workflows.
Benefits
- Perks on Perks:**
- Competitive salary and hybrid work model – come hang out in our Athens office or work remotely from anywhere in European economic Area (EU, Switzerland etc.) or UK (up to 6 weeks per year).
- Training budget to level up your skills from the top tech partners in the market (Microsoft, AWS, Salesforce, Databricks etc.) – whether it’s certifications or courses, we’ve got you covered.
- Private insurance, top-tier tech gear, and the chance to work with a stellar crew.
- Ready to create some data magic with us? Hit that apply button and let’s get started.
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