Data Scientist – Customer & Marketing Analytics

Satori Analytics

Data Scientist driving customer and marketing analytics projects at Satori Analytics. Collaborating with various teams to build actionable segmentation and targeting solutions based on customer data.

Posted 7/31/2026full-timeRemote • 🇬🇷 GreeceMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in customer segmentation, clustering techniques, and explainable AI, with a strong ability to translate complex analytical findings into actionable business insights. Proficient in Python, R, SQL, and data visualization tools, with a solid grounding in applied statistics and marketing KPIs.

Highest-signal resume keywords

Customer SegmentationClustering TechniquesExplainable AI (SHAP)Applied StatisticsPython or R

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Clustering AlgorithmsBehavioural AnalyticsMetrics EvaluationData AnalysisStatistical TestingModel EvaluationSQLData VisualizationPropensity ModellingA/B Testing

Soft Skills

Clear CommunicationDocumentation SkillsIndependent WorkProactive Risk Management

Tools & Technologies

Power BITableauAzureAWSGCPDatabricksGitSparkPySparkDask

Industry Keywords

Customer AnalyticsMarketing AnalyticsCRMCustomer Lifecycle ManagementFMCGRetailLarge-Scale Transaction Data

Tech Stack

Tools & technologies

AWSAzureCloudGoGoogle Cloud PlatformPySparkPythonSparkSQLTableau

About the role

Key responsibilities & impact

**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.

Requirements

What you’ll need

**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

Comp & perks

**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.