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Customer Loyalty/ Transaction Lead Data Scientist

Posted 2 weeks ago by NES Fircroft

Customer Loyalty/ Transaction Lead Data Scientist – 12 Months Contract – Remote

Inside IR35 via umbrella

Remote

Must be eligible to work in the UK

Start ASAP

40 hrs week

Must Have

  • Advanced SQL for high-volume customer, payment, loyalty and transaction analysis.
  • Strong Python for statistical analysis, matching, weighting, cohort analysis and reproducible data products.
  • Hands-on Databricks/Spark or PySpark experience for notebooks, Delta tables, workflows and scheduled analytical pipelines.
  • Working proficiency with Git/Azure DevOps, pull requests and controlled production changes.
  • Strong data-validation, reconciliation and audit-trail practices.

Nice to have

  • Loyalty economics, retail fuel/convenience or CRM-domain experience.
  • Power BI or certified reporting-layer experience.
  • Production pipeline design beyond analytical notebooks, including Delta MERGE, idempotency and incremental processing.
  • Experimentation or uplift-model validation experience.
  • BNA or customer-decisioning exposure.

MUST HAVE

  • high-volume customer, payment, loyalty and transaction analysis

Data Scientist Role Overview

Lead Data Scientist - Customer Intelligence, Incrementality & Value Measurement Primary focus: SCI/customer analytics, incrementality, CLV/RFM, customer and margin reconciliation, dampening methodology, scenario planning and multi-market value measurement.

The role owns the analytical bridge between SCI customer and transaction data, CLV/RFM segmentation, incrementality methodology, Finance margin assumptions and leadership-facing value estimates.

It must be able to determine not only the result, but why sources differ, whether the estimate is methodologically defensible, and how it can be reproduced and operationalised.

Rate:
Not specified
Location:
United Kingdom
IR35 Status:
Inside
Remote Status:
Remote
Industry:
Data & Analytics
Seniority Level:
Not Specified

Take-Home Pay

Not Available

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