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Data scientist - leading consumer fintech

Slough
Harnham Search & Selection
Data scientist
Posted: 4 May
Offer description

Do you want to build ML models that directly drive real customer and lending decisions?

Have you worked on customer prediction problems like pricing, forecasting, or segmentation?

Are you ready to join a fast-paced fintech where Data Science sits at the core of the business?


We’re hiring a Data Scientist (1–2 years experience) for a well-established UK consumer fintech operating across lending and credit products. The business is profitable, highly data-driven, and known for its strong engineering and modelling standards. With continued international growth, there is significant opportunity to work on impactful, production-level problems.


This is not a reporting or BI role. You’ll be building models that directly influence customer outcomes, risk, and growth.


The Role

You’ll join a core modelling team focused on applied machine learning, owning models end to end and working closely with Product and business stakeholders.


Key Responsibilities

* Build and deploy production ML models used in live decision-making
* Work on customer prediction problems including pricing, forecasting, and segmentation
* Develop models using Python and SQL on large-scale datasets
* Own the full model lifecycle from data extraction to deployment and monitoring
* Collaborate with Product and commercial teams to drive decisions


Candidate Profile

* 1–2 years industry experience as a Data Scientist
* Strong academics (Russell Group or equivalent, STEM degree)
* Experience building ML models in Python and SQL
* Background in customer prediction (pricing, forecasting, segmentation) or credit risk
* Curious, high-energy problem solver with strong ownership mindset


Key Details

* Salary: £60k–£65k base + equity
* No bonus, minimal benefits
* Working model: Hybrid (Tuesday–Thursday in office, non-negotiable)
* Tech stack: Python, SQL, applied ML
* Visa sponsorship: Not currently offered


Interested? Please apply below.

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