--- title: 'Data Scientist - UK at Focal Systems' canonical: 'https://feeny.ai/job/data-scientist-uk-focal-systems-united-kingdom-fqyjrr2v6tk7' type: 'job' last_seen: '2026-10-17' --- # Data Scientist - UK at Focal Systems - **Company:** Focal Systems - **Location:** United Kingdom - **Work type:** remote - **Posted:** 2026-06-08 - **Last confirmed live:** 2026-10-17 - **Apply:** https://job-boards.greenhouse.io/focalsystems/jobs/6016008004 ## Job description Type: Full-time, salaried employment Location: Remote in the UK only. Salary Range: £60,000 to  £70,000 + stock options Focal Systems is the industry leader in retail AI solutions. We are headquartered in San Francisco, California with operations in Canada and the UK, and a tech-hub in Poland. We are a Deep Learning first company. Our mission is to automate and optimize brick and mortar retail using deep learning computer vision. Focal Systems has been deployed at scale with some of the top retailers in the world. We seek smart, creative and passionate people who want to help build a great and enduring company and deploy Deep Learning to the world! ## About the Role As a Senior Data Scientist on our Analytics team, you will own end-to-end problems that combine applied statistics, experimentation, and machine learning to drive measurable improvements in how our retail AI products perform in the real world. You will work on ambiguous, open-ended questions, define the right approach, and deliver insights and models that influence the roadmap of Product, Engineering, and Operations. This is a senior individual contributor role. You will set the technical direction for your projects, partner with cross-functional stakeholders, and act as a force multiplier for analytics quality across the company. ## What We Are Looking For - You are a rigorous thinker who treats data as evidence, not decoration, and is comfortable telling a clear story about uncertainty - You have strong technical chops in SQL and Python, and you reach for the right tool, statistical, experimental, or ML, based on the problem in front of you - You can design experiments, reason about causality, and identify when a correlation is enough and when it is not - You are comfortable owning ambiguous, open-ended problems and breaking them down into a credible plan - You communicate findings crisply to technical and non-technical audiences, in writing, in dashboards, and in person - You raise the bar for the team through code review, methodology review, and mentorship of less senior analysts and scientists ## What You Will Be Doing - Own analytical problems end to end from problem framing and metric definition through data acquisition, modeling, validation, and stakeholder rollout - Build predictive and inferential models such as forecasts, propensity and uplift models, and survival or duration analyses, where they meaningfully improve a product or operational decision - Develop statistical methods and reusable analyses for measuring performance, including detection accuracy, intervention impact, and downstream operational outcomes - Partner with Product, Engineering, and Operations to define key metrics, implement new features, and translate business questions into well-scoped analytical work - Audit system outputs and provide structured feedback that improves product accuracy and reliability - Communicate findings through dashboards, written analyses, and stakeholder presentations that lead to concrete decisions - Help define best practices around data quality, experimentation, modeling, and reproducibility, and contribute to the team’s data contracts and SOPs ## Requirements - 5+ years of experience as a Data Scientist, Quantitative Analyst, or similar role, with a track record of shipping analyses and models that changed product or business decisions - Strong proficiency in SQL, including complex CTEs, window functions, and query optimization - Strong proficiency in Python for data work, including pandas, NumPy, and experience with statsmodels or other relevant tools - Solid grounding in applied statistics: hypothesis testing, regression, experimental design, and uncertainty quantification - Experience designing and analyzing A/B tests or other controlled experiments in a product setting - Experience building at least one class of predictive model end to end, for example forecasting, classification, or propensity modeling - Experience with data visualization and BI tools, and the ability to turn an analysis into a clear narrative - Excellent written and verbal communication, with the ability to influence cross-functional partners without authority - Ability to work independently, manage multiple priorities, and drive ambiguous projects to completion ## Nice to Have - Experience with Snowflake or a comparable cloud data warehouse - Experience with Sigma, Looker, or similar BI tools - Experience with database engineering/architecture - Background in retail, logistics, marketplaces, or other operationally complex environments - Experience mentoring analysts or junior data scientists ## Why Focal Systems Strong Values and Mission - We are a tightly-knit team with an ambitious mission and a strong set of core values, which define our approach to business and have successfully guided us since inception. Exceptional Team - We are a team of hard-working, fun-loving professionals from some of the most eminent universities, research labs, and tech companies of our time. We pride ourselves on recruiting exceptional individuals to help us redefine the state-of-the-art. Outstanding Partners - We work with 10+ of the largest retailers in the world and have a world-class roster of investors, advisors and partners to support & advise us in our endeavors. ## What we offer We care deeply about the health, happiness, and wellbeing of all of our employees. We offer: - Competitive Salary & Attractive Stock - Generous Paid Time Off - Pension - Sick Leave - Parental Leave - Learning and Development Budget ## About Focal Systems ## Company Overview - **One-liner**: Focal Systems provides AI-powered computer vision solutions that give brick-and-mortar retailers real-time shelf visibility to optimize product availability, reduce waste, and automate store operations. - **Entity Type**: Private (Startup, funding stage not explicitly stated in sources) - **Headquarters**: San Francisco, California, USA - **Founded**: Not publicly available - **Founders**: Not publicly available ## Core Business - **Primary industry/industries**: Retail technology, computer vision, artificial intelligence, store operations automation - **Target customers**: B2B, large brick-and-mortar retailers globally - **Mission or purpose statement**: "To automate and optimize brick and mortar retail using computer vision" [greenhouse.io](https://boards.greenhouse.io/focalsystems) ## Products & Services - **Focal AI-Powered Shelf Cameras**: Hardware and software solution that continuously scans product availability on shelves, ensuring shelves are stocked and planograms are followed. Provides real-time aisle-level insights. - **Impact Dashboard**: A management dashboard for measuring and visualizing store performance, out-of-stock duration, sales recouped, task completion, compliance, and presentability. - **Action Tool**: An AI-driven operating system that automates task management, prioritizes restocking, and ensures the most critical tasks are completed first. Integrates with stock keeping, replenishment, ordering, staff management, labor planning, merchandising, and planogram compliance. ## Market Standing - **Valuation/Market Cap**: Not disclosed - **Key Metric**: Total Funding — Not publicly available - **Notable Investors/Partners**: Works with "some of the largest retailers in the world" and has a "world-class roster of investors, advisors and partners" [greenhouse.io](https://boards.greenhouse.io/focalsystems). Named Confluent’s Inaugural Data Streaming Startup of the Year [focal.systems](https://focal.systems/). - **Growth Signals**: Deployed at scale with top global retailers; expanding globally with field operations roles in the UK; hiring across engineering, data science, and customer support roles in multiple countries (US, UK, Poland, Canada, Australia). ## Competitive Advantages - **Real-time, actionable AI**: Unlike many analytics-only solutions, Focal's system directly automates tasks and prioritizes work for store associates, bridging the gap from insight to action. - **End-to-end integration**: Covers shelf scanning, inventory management, labor planning, and planogram compliance in a single platform. - **Deep learning expertise**: The company describes itself as a "deep learning company" focused on retail, suggesting a proprietary computer vision stack. ## Strategic Focus - **Global expansion**: Active hiring in the UK, Poland, and other regions indicates a push into new markets. - **Product innovation**: Continuously pushing boundaries of AI and machine learning to develop new retail solutions. - **Customer success**: Emphasis on real-world impact metrics like reduced out-of-stock duration and improved workforce efficiency. ## Why Work Here - **Culture**: Described as mission-driven, collaborative, and ego-free. The company says "egos take a backseat to teamwork" [focal.systems](https://focal.systems/about-focal/). - **Work model**: Remote-friendly with roles listed as remote in the UK and Poland. A San Francisco headquarters exists with weekly lunches for HQ-based team members. - **Benefits**: - Market-benchmarked and transparent salaries - Medical, dental, and vision insurance (USA); supplemental medical coverage in Canada, Australia, and UK - Flexible time off with a minimum of three weeks per year - Paid company-wide shutdown the last week of the year - Learning and development stipends - Equity grants for all full-time team members (viewed as co-owners) - Offsites for team collaboration and strategic planning - **Growth**: Professional growth plans, stretch assignments, and the chance to learn from industry leaders. The company wants to "be an accelerant for your career." - **Team**: Global team of experts from top retailers, best-in-class software companies, and premier research institutions. ## Sources 1. [focal.systems](https://focal.systems/) 2. [focal.systems/about-focal](https://focal.systems/about-focal/) 3. [greenhouse.io](https://boards.greenhouse.io/focalsystems) 4. 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