At a Glance
- Tasks: Lead data science projects, build models, and communicate with clients as a technical expert.
- Company: Fospha, a leader in online retail measurement solutions.
- Benefits: Competitive salary, career development framework, and a collaborative team environment.
- Other info: Opportunity for mentorship and growth within a supportive team.
- Why this job: Make a real impact on marketing strategies for well-known brands using advanced methodologies.
- Qualifications: 3-5 years of data science experience, strong ML knowledge, and Python/SQL skills.
The predicted salary is between 59400 - 72600 £ per year.
Fospha is dedicated to building the world's most powerful measurement solution for online retail. For over a decade, we've helped teams make smarter decisions with full-funnel marketing insights, forecasting, and optimisation. With Fospha, every team moves faster and grows smarter.
We're looking for a Data Scientist to join Fospha's Data Science team in London. Fospha builds marketing measurement products for ecommerce brands — attribution, marketing mix modelling, incrementality testing, and brand impact measurement. Our Data Science team owns the models behind all of it, from methodology through to production code. You will work across our technical stacks and own maintaining and growing the codebases that power our product and solutions. This role suits an established data scientist who wants to own things properly. You'll lead larger production projects, choose the modelling approach rather than being handed it, and talk to clients as the modelling expert in the room — supported by a team that reviews each other's work seriously, and a company that rewards high agency with ownership.
What you'll do:
- Lead larger production projects end to end — scoping, building, and shipping production-level code.
- Choose the modelling approach — independently selecting and applying the right method within our suite.
- Resolve bugs and queries independently — including in parts of the codebase you didn't write.
- Use AI as leverage, not as a crutch — solving coding tickets quickly and building automation workflows that save the team time.
- Work with QA properly — using our automated tooling efficiently and flagging the gaps in it.
- Communicate as a modelling expert — confidently and independently, with clients and colleagues.
- Help develop the people around you — code review, methodology critique, and hands-on support for less experienced colleagues.
What we're looking for:
Essential:
- Solid commercial data science experience — typically 3–5 years, with a track record of shipping models into production.
- Strong ML knowledge across multiple algorithm families.
- Strong Python and SQL, with the ability to lead on production-level code.
- Able to debug and resolve issues independently across unfamiliar repositories.
- Strong AI fluency — you solve tickets quickly with it and build automation workflows with it.
- Confident, independent communication with clients and stakeholders.
- Emerging mentorship — you're ready to develop junior colleagues.
- Genuine attention to detail.
Nice to have:
- Bayesian modelling experience, particularly hierarchical models.
- Experience with AWS or comparable cloud tooling.
- Familiarity with automated QA tooling and test coverage practices.
- Experience with marketing, ecommerce, or advertising data.
Not required:
Experience with attribution methodology, MMM, incrementality testing, or Bayesian modelling is genuinely an advantage at this level — but it isn’t a filter.
How You'll Grow:
We run a published Data Science Career Development Framework with six levels. You'd join at Career, where the expectations are:
- AI Fluency & Tooling: Leverages AI to solve coding tickets quickly.
- Machine Learning & Modelling: Strong ML knowledge across multiple algorithm families.
- Engineering & Codebase: Leads on larger coding projects and tickets with production-level code.
- Stakeholder & Communication: Confidently and independently communicates with clients and colleagues.
- Job Complexity: Consistent contributor and respected knowledge holder.
- Supervision: Demonstrates initiative in accepting and planning work.
Throughout, we look for the same core behaviours: concise communication, collaboration, problem solving, critical thinking, growth mindset, attention to detail, time management, and initiative.
Why Fospha:
- Real methodological depth.
- Ownership at the methodology level.
- Published career framework.
- A team that reviews each other's work properly.
- Direct client impact.
Data Scientist employer: Fospha
Fospha is an exceptional employer for Data Scientists, offering a dynamic work environment in London where innovation and ownership are at the forefront. With a strong focus on employee growth through a published career development framework, team collaboration, and direct client impact, Fospha empowers its employees to lead significant projects and make meaningful contributions to the world of ecommerce marketing measurement. The culture promotes continuous learning and mentorship, ensuring that every team member can thrive and advance their career while working on cutting-edge methodologies.
