Head of Data Science

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 mighty NHS to give their teams access to fairer financial services - all 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 at scale-up pace, but with a social conscience. Some of the world's leading financial charities and impact funds were our founding investors, and we operate on a social charter - which means every product we build has to improve financial health and reduce the $5.6bn ‘premium’ lower-income earners pay for financial services each year.

You’d be joining a team of over 200 passionate, ambitious people, across Europe and the USA, building a category-leading fintech product and all united by that same mission.

The Opportunity:

Wagestream is hiring a hands-on Head of Data Science to lead and grow our Data Science team and drive data-informed decision-making across the organisation. This is a critical leadership role responsible for setting the direction of Data Science at Wagestream, building a high-performing team, and ensuring the delivery of impactful data products.

We believe that Data Science consists of 4 key elements:

1. Data Analysis
2. Includes data cleansing, writing complex SQL queries and using commercial understanding to deliver actionable insights.
3. Data Visualisation
4. Includes creating dashboards and reports in various formats so as to make data more understandable to all stakeholders.
5. Data Engineering
6. Includes writing Python, following SDLC best practices, using Git, and creating data products in dbt.
7. Applied Statistics & Machine Learning
8. Includes experiment design and analysis, causal inference, hypothesis testing, feature engineering, and ML model development and deployment.

You don't have to be great at all of these areas for us to want to talk to you. We want to help you grow and develop your skills in areas you are less familiar with over time.

The Team:

You will lead and manage our team of embedded Data Scientists, and report directly to the CTO. You will collaborate closely with other department heads (e.g. Operations, Product, Engineering) to align data science initiatives with overall business objectives.

What will you be doing?

Leadership & Management

• Build, mentor, and manage a team of Data Scientists, fostering a culture of collaboration, innovation, and continuous learning.
• Set clear goals and performance expectations for the team, providing regular feedback and coaching.
• Identify, scope and prioritise high-impact data science projects that drive business value.
• Champion the use of data and analytics throughout the organisation.
• Stay abreast of industry trends and emerging technologies in data science, machine learning, and AI.

Technical Execution & Oversight

• Implement a robust data governance framework, ensuring quality, cataloging, and discoverability.
• Enforce data compliance standards, including PII masking, data obfuscation, and RBAC.
• Oversee the design, development, deployment, and maintenance of data products, including dashboards, reports, dbt models, and machine learning models.
• Ensure the quality, accuracy, and reliability of data analysis and modelling.
• Collaborate with the Software Engineering team to build and maintain a robust data infrastructure.
• Oversee the development of reports and dashboards that provide clear information about team progress on various KPIs.
• Oversee the analysis of A/B tests and hypothesis testing to help us improve our product.
• Provide strategic direction and oversight for the development of our bespoke LLM-based Customer Support agent.

Our Tech Stack:

• Data: dbt, Snowflake, PostgreSQL, Sigma, Redash
• Code: Python
• Infra: AWS, GitHub

What experience might you have?

• Strong mathematical skills, ideally grounded in a quantitative STEM degree such as Mathematics, Computer Science, Physics or Engineering.
• Previous management experience.
• Previous professional experience in a Data Science, Data Engineering, Analytics Engineering, Data Analysis or Software Engineering role.
• Previous professional experience using OLTP and OLAP databases, and dbt.
• Advanced SQL skills, covering window functions, CTEs, recursion and performance optimisation.
• Advanced Python skills, covering functional programming and testing.
• Good communication skills, enthusiasm, humility and a desire to learn.
• A preference to work in a fast-paced and unstructured environment.

Nice to haves:

• Advanced ML skills, covering techniques such as gradient boosting, random forests and neural networks.
• Prior experience with Snowflake.
• Prior experience deploying ML models.

Salary: Competitive & dependent on seniority, upward from £125,000 + equity

Working Policy: Hybrid, with three office days per week

Location: Central London

Benefits:

• 25 Days Annual Leave in addition to public holidays (up to 5 day rollover), as well as flexible time off allowances for any ad-hoc childcare/family/caring needs
• 10 days Annual Leave Buy-Back scheme
• 24 weeks' paid Maternity Leave and 4 weeks paid Paternity Leave for employees with over 12 months service
• Special Leave for In Vitro Fertilisation (IVF) and other fertility treatments
• Sabbatical scheme
• Paid leave to volunteer
• Work from Abroad policy
• Private Healthcare including comprehensive mental-, physical
• Salary sacrifice to pension, as well as bonus exchange to Pension: reap even more rewards of any bonus by paying into your pension & save on Tax and NI + added compound growth
• Season Ticket Loan
• The best benefit of all, access to Wagestream!
• Access to Salary Sacrifice Schemes via ThanksBen: THE Benefits marketplace. Choose the benefits you want, when you want. Pay less tax, receive more value

Additional:

• Additional Pension Payments
• Workplace nurseries
• Cycle to Work
• Home and Tech Scheme
• Healthcare cash plans, etc

At Wagestream we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Wagestream is an equal opportunity workplace. We are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, or veteran status.