Senior Data Scientist

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Senior Data Scientist

role at

Wagestream .
This range is provided by Wagestream. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range

Direct message the job poster from Wagestream.
Wagestream is on a mission to bring better financial wellbeing to frontline workers.
We partner with some of the world’s most famous employers, like Bupa, Burger King, Greene King, and the NHS, to give their teams access to fairer financial services—built around flexible pay. Over three million people can now choose how often they’re paid, track their shifts and earnings, start saving, use budgeting tools, get free financial coaching, and access fairer financial products—all in one financial wellbeing super-app.
Wagestream is unique: VC-backed and growing rapidly, but with a social conscience. Our founding investors include leading financial charities and impact funds. We operate under a social charter, ensuring every product we develop aims to improve financial health and reduce the $5.6bn ‘premium’ paid annually by lower-income earners for financial services.
You’d join a team of over 200 passionate, ambitious people across Europe and the USA, building a category-leading fintech product united by our mission.
The Opportunity:
We are hiring multiple Data Scientists to embed within our Operations divisions and support leadership in making data-informed decisions. We are interested in Senior and Lead Data Scientists.
We believe Data Science involves four key elements:
Data Analysis: including data cleansing, complex SQL queries, and delivering actionable insights.
Dashboard and report creation to make data understandable for all stakeholders.
Writing Python, following SDLC best practices, using Git, and creating data products in dbt.
Experiment design, causal inference, hypothesis testing, feature engineering, and ML model development and deployment.
You don’t need to excel in all areas initially; we support your growth in less familiar skills over time.
Data Scientists will primarily focus on Data Analysis & Visualization, while Lead Data Scientists should have strong expertise across all four elements.
The Team: Operations
Reporting to the VP of Operations, you will collaborate closely with Data Science and Software Engineering teams to deliver impactful solutions.
What will you be doing?
Building reports and dashboards to track KPIs.
Creating data products (dbt models) for the organization.
Developing classification and regression ML models using techniques like random forests and gradient boosting.
Identifying data gaps and working with Software Engineers to address them.
Analyzing A/B test results and hypothesis testing.
Contributing to the development of our LLM-based Customer Support agent.
Using Python; infrastructure includes AWS and GitHub.
What experience might you have?
Strong quantitative skills, preferably with a STEM degree (Mathematics, Computer Science, Physics, Engineering).
Experience in Data Science, Data Engineering, Analytics Engineering, or Software Engineering roles.
Proficiency in SQL and Python.
Advanced SQL skills (window functions, CTEs, recursion, performance optimization).
Good communication, enthusiasm, humility, and eagerness to learn.
Ability to thrive in a fast-paced, ambiguous environment.
Nice to haves:
Advanced Python skills (functional programming, testing).
Advanced ML skills (gradient boosting, neural networks).
Experience with dbt and Snowflake.
Deploying ML models.
Experience in consumer credit or lending products.
Salary:

Dependent on seniority, starting from £60,000 plus equity.
Career progression:

DS1 (Junior) to DS6 (Head of Data Science).
Work policy:

Hybrid, with three office days per week.
Location:

Central London.
Additional benefits include generous leave, private healthcare, pension contributions, season ticket loans, and access to Wagestream.
Wagestream celebrates diversity and is committed to equal opportunity employment.

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