--- title: 'Junior Data Scientist at Fospha' canonical: 'https://feeny.ai/job/junior-data-scientist-fospha-london-6f379jphv4f6' type: 'job' last_seen: '2026-09-10' --- # Junior Data Scientist at Fospha - **Company:** Fospha - **Location:** London, United Kingdom - **Posted:** 2026-08-20 - **Last confirmed live:** 2026-09-10 - **Apply:** https://job-boards.greenhouse.io/fosphamarketing/jobs/8143897 ## Job description 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. ## About the role We're looking for a Data Scientist to join Fospha's Data Science team in London, working within our Stream 3 workstream. 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 have the chance to work across our technical stack to make real code impacts on codebases. This role suits someone with some commercial data science experience behind them who wants to go deeper. You’ll take on interesting but challenging work with a supportive team structure and a company that rewards high agency with ownership. Team: Data Science Level: Developing (Data Science Career Development Framework) Location: London ## What you'll do - Own moderately difficult tickets end to end — analytical investigations, model backtesting, production bug fixes, and pipeline work, with decreasing need for step-by-step direction - Debug systematically across our codebases — including repositories you're only partly familiar with, using AI tooling to get up to speed quickly - Write and review production code — Python and SQL that avoids technical debt, plus reviewing AI-assisted code so it lands with minimal bugs - Use our QA automation and cloud tooling effectively — running validation properly and understanding the data science parts of our AWS pipelines - Communicate with clients and colleagues — explaining methodology and findings directly, with only minor assistance from senior colleagues - Push for clarity up front — working directly with other teams to pin down acceptance criteria and requirements, rather than sitting blocked waiting on them - Start becoming an internal data science champion — the person other teams come to on the areas you own ## What we're looking for Essential - Some commercial data science experience — typically 1–2 years, or a strong placement/internship record alongside a quantitative degree - Strong Python and SQL, with the ability to collaborate on shared code and avoid technical debt - Deep knowledge of a handful of machine learning algorithms — not breadth for its own sake, but real understanding of a few methods and when they apply - Able to systematically debug unfamiliar code, using AI tooling to accelerate rather than to guess while still understanding problem fully - Strong AI fluency — you understand how to optimally start a task with AI, you use it to unblock cross-team dependencies, and you always QA the output for accuracy and brevity before it goes anywhere - Confident completing work independently once scope is agreed - Able to communicate with clients and colleagues with only minor assistance - Genuine attention to detail — much of this work involves noticing when a number is wrong ## Nice to have - Experience with AWS or comparable cloud tooling - Familiarity with automated QA tooling and test coverage practices - Any experience with marketing, ecommerce, or advertising data - Exposure to Bayesian methods, marketing mix modelling, or experimental design Not required You do not need prior experience with marketing mix modelling, attribution methodology, incrementality testing, or Bayesian modelling. These are taught here, and we'd rather hire someone who learns fast than someone who arrives pre-loaded. ## How you'll grow We run a published Data Science Career Development Framework with six levels. You'd join at Developing, where the expectations are: AI Fluency & Tooling: Understands how to optimally start all relevant tasks with AI; confident completing work independently; uses AI to push for acceptance criteria and limit cross-department dependencies; always QAs AI output for accuracy and brevity. Machine Learning & Modelling: Deep knowledge of a handful of algorithms, and familiarity with the full Fospha model suite. Engineering & Codebase: Systematically debugs issues with AI support, even in partly familiar repositories; uses supplied AWS tooling efficiently and understands the data science parts of the pipelines; uses existing QA automation effectively; avoids technical debt and collaborates well on code; reviews AI-assisted code so it ships with minimal bugs. Stakeholder & Communication: Communicates with clients and colleagues with minor assistance. Job Complexity: Undertakes moderately difficult tickets while starting to become an internal data science champion. Supervision: Receives detailed instruction, but becomes progressively less dependent on senior colleagues. Progression to Career level is against explicit, published criteria — leading larger production projects, resolving bugs independently, and communicating as a modelling expert in your own right. You'll know what you're working towards from your first week. 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. Bayesian attribution, MMM, geo lift testing, and causal inference are our day job, not a side project. You'll be working on all of it, not adjacent to it. - Published career framework. No guessing what the next level requires or when you'll get there. - A team that reviews each other's work properly. Code review and methodology critique from people who care about getting the model right. - Direct client impact. The models you build and maintain drive real budget decisions at brands you'll recognise. ## About Fospha ## Company Overview - **One-liner**: Fospha provides a full-funnel marketing measurement operating system for retail commerce, enabling brands to measure and optimise the impact of every impression and click across channels and marketplaces. - **Entity Type**: Private (backed by venture builder Blenheim Chalcot; post-seed/revenue-stage with 200+ customers) - **Headquarters**: London, United Kingdom (with offices in the US and across three continents) - **Founded**: 2014 - **Founders**: Founded by Blenheim Chalcot; led by CEO Sam Carter ## Core Business - **Primary industry**: Marketing measurement & analytics (SaaS for retail commerce) - **Target customers**: B2B – mid-market to enterprise retail brands (DTC, Amazon, TikTok Shop, etc.) such as Gymshark, Huel, and Dyson - **Mission or purpose**: To give brands the confidence to spend their full-funnel budgets and drive long-term profitable growth by providing transparent, privacy-safe, daily measurement. ## Products & Services - **[Daily MMM (Core & Beam)](https://www.fospha.com/)**: Always-on Media Mix Model delivering impression-led, full-funnel measurement at daily and ad-level granularity. Deterministic, correlative, and causal models working together (ensemble methodology). - **[Prism – Automated Budget Optimisation](https://www.fospha.com/)**: Bayesian saturation curves and marginal return forecasts that automatically shift budgets away from underperforming campaigns, improving channel efficiency. - **[Halo – Marketplace Measurement](https://www.fospha.com/)**: Incremental models that quantify how paid media drives sales across Amazon, TikTok Shop, and retail marketplaces, capturing cross-channel halo effects. - **[Glow – Brand Measurement](https://www.fospha.com/)**: Causal reasoning models to prove the revenue impact of brand-building spend. - **[Fospha AI](https://www.fospha.com/)**: In-dashboard conversational AI (marketing strategist) and MCP integration allowing teams to query data via Claude, ChatGPT, etc. - **[Science & Strategy Squad](https://www.fospha.com/about-fospha)**: Dedicated measurement experts running incrementality tests, standalone MMMs, and setting the learning agenda. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Over $2.5 billion in marketing spend under management (as of 2025); 200+ customers across 26 countries - **Notable Investors/Partners**: Founded and backed by **Blenheim Chalcot**; certified partner of **Meta, TikTok, and Snapchat**; customers include Gymshark, Huel, Dyson - **Growth Signals**: - 150+ employees across three continents (London, US, and other offices) - $2.5bn spend under management (up from earlier $4bn claim – likely cumulative milestone) - Acquisitions: iJento (web analytics, 2016) and another unnamed acquisition - Expanded to 200+ customers and three continents by 2025 - Launched Fospha Pro (full-funnel MTA/MMM + predictive planning) and integrated AI capabilities ## Competitive Advantages - **Glass-box transparency**: Every model layer, validation metric, and decision rule is visible to clients – no black boxes. - **Privacy-first from day one**: Moved away from pixel-based tracking over a decade ago; compliant with GDPR, CCPA, iOS14, and preparing for Google’s Privacy Sandbox. - **Ensemble methodology**: Combines deterministic click modelling, impression modelling, Bayesian saturation curves, and causal reasoning in a single always-on system. - **Daily, ad-level granularity**: Unlike legacy MMMs that run quarterly, Fospha delivers full-funnel results daily at the ad level, enabling near-real-time optimisation. - **Marketplace coverage**: Uniquely measures cross-channel halo effects on platforms like Amazon and TikTok Shop, which pixel-based tools miss. ## Strategic Focus - **Current priorities**: Deepening automation (Prism), expanding AI capabilities (Fospha AI and MCP integrations), and strengthening marketplace measurement (Halo). Scaling globally with a growing customer success and sales team. - **Direction for growth**: Continue to replace legacy attribution and MMM tools in retail commerce; add more retail media networks and sales channels; increase spend under management and headcount. ## Why Work Here - **Culture highlights**: Values include “Candour with caring”, “Seek inclusion & diversity”, “Customer at the heart”, and “Work hard, work well, work together”. Emphasis on continuous learning, professional growth, and collaborative innovation. - **Remote/hybrid/office policy**: Offices in London (HQ), Austin (US), and other locations. Roles span across Customer Success, Sales, Marketing Science, Product, and Central Operations. Likely hybrid/flexible depending on role (exact policy not specified but offices are active). - **Notable perks**: Opportunity to work with a team of 150+ data scientists and marketing experts; impact on billion-dollar spend decisions; close partnerships with major ad platforms; dynamic growth phase with significant career advancement potential. ## Sources 1. [fospha.com](https://www.fospha.com/) 2. [fospha.com/about-fospha](https://www.fospha.com/about-fospha) 3. [fospha.com/life-at-fospha](https://www.fospha.com/life-at-fospha) 4. [cbinsights.com](https://www.cbinsights.com/company/fospha) 5. 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