Senior Data Analyst, Lifecycle

Finom

. Own measurement and experimentation for customer activation and retention .

Posted 11/3/2026full-timeRemote • Germany, Spain, Romania, Serbia, PolandSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in measurement and experimentation for customer activation and retention, utilizing strong SQL and Python skills to design and analyze experiments. Proficient in building segmentation models and automating reporting processes to enhance customer engagement.

Highest-signal resume keywords

Strong SQLPython ProgrammingExperiment DesignBI ExperienceStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Experiment DesignCausal Inference MethodsPredictive ModellingClusteringSegmentation

Soft Skills

CuriosityOwnership

Tools & Technologies

Power BITableauDatabricksBraze

Industry Keywords

Customer ActivationCustomer RetentionA/B TestingChurn ScoringAudience Segmentation

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Own measurement and experimentation for customer activation and retention
Join activation and retention initiatives from CRM, growth, and product before development begins
Define primary metrics and assess detectability using historical data
Design and analyse experiments end to end, including hypotheses, guardrails, audience splits, MDE, power, stopping rules, and readouts
Correct for channel and engagement bias
Apply causal inference methods when clean A/B testing is not possible, including diff-in-diff, matching, synthetic control, and geo designs
Generate and launch experiments across onboarding and the customer lifecycle
Convert successful one-off experiments into recurring segmented flows
Build segmentation, propensity, churn, and dormancy scoring models
Develop next-best-action logic and measure performance against current rules
Automate audience refresh jobs, readout templates, and Activation, Onboarding, and Retention dashboards
Ship models through scheduled Databricks jobs and downstream tools such as Braze
Bring engagement data back into the warehouse to close the loop

Requirements

What you’ll need

Strong SQL and Python
Git-based warehouse workflow with code review
Experiment design, statistics, and defensible metric design
BI experience with Power BI, Tableau, or similar
Stakeholder management and business sense
Curiosity and ownership
Causal inference methods and understanding of when each is valid (nice to have)
Clustering and segmentation used in production (nice to have)
Predictive modelling with honest validation; uplift modelling is a plus (nice to have)
Braze or comparable CRM platform experience (nice to have)

Benefits

Comp & perks

Continuous personal and professional development resources and opportunities
Remote or hybrid work flexibility across Europe
Stock Options Program available to every team member
Constant support and care
Modern, friendly, and eco-conscious corporate culture
Work & Swim Program: one month in a corporate apartment in Cyprus