Senior Data Scientist - Hybrid, London
Data Science
London, UK
Who We Are:
Datassential is a leading global intelligence platform for the food and beverage industry. Leveraging billions of data points and cutting-edge AI, we provide a suite of innovative solutions that empower more than 90% of the world's largest food and beverage brands to develop, market, and sell their products more effectively.
Based in Chicago, USA, Datassential has expanded its global reach through strategic acquisitions of CHD Expert (France) in 2022 and Brizo Data, Inc. (Canada) in 2025. In 2024, we secured investment from top-tier private equity firms New Mountain Capital and Endicott Capital—a milestone that fuels our accelerated product roadmap and strengthens our research and development, enabling us to deliver even greater value to our clients.
This role is hybrid and based in London, with regular on-site presence required 2-3 days per week. Candidates must be located within commuting distance of our London office.
Why You Should Join Us:
Our data science team works with one of the most distinctive datasets in the food and beverage industry: deep, longitudinal operator data spanning years of menu, concept, and market behaviour across global markets. The EMEA region is a growth priority for Datassential, and this role sits at the centre of how we build and deliver intelligence for that market.
You will have the rare combination of genuine domain depth to draw on, a wealth of historical data to work with, and a direct line to how your outputs reach customers through our sales intelligence platform. We are passionate about data, committed to doing the work well, and have a 'we can do anything' attitude. We value work-life balance, and you will be joining a team and company that wants you to grow.
What We Need:
We are seeking a full-time Data Scientist to join our EMEA team, focused on building the derivative data elements and modelled insights that power our global sales intelligence platform. You will work across a variety of existing data sources—as well as newly acquired data—applying statistical analysis and machine learning to extract signals that our customers cannot get anywhere else.
This is not a research-only role. You will own your models from initial design through to operationalisation, working with our data pipeline team to ensure outputs are integrated reliably into production. You will also collaborate with and provide mentorship to other data scientists on the global team, helping to raise the overall quality and consistency of modelling practices across the company.
Who You Are:
A rigorous data scientist who is equally comfortable developing models and seeing them through to production-grade outputs
Energised by the challenge of building on rich longitudinal data to surface insights that genuinely change how businesses think about food and foodservice
Fluent in modern ML and AI techniques—and honest about when a simpler statistical approach is the right one
Curious about the foodservice industry and motivated by the idea that your models will directly inform strategic decisions for some of the world's largest food and beverage brands
Comfortable working across the full modelling lifecycle: from hypothesis and feature engineering through validation, iteration, and handoff into production pipelines
A collaborative partner who can communicate model logic, assumptions, and limitations clearly to non-technical stakeholders
Willing to mentor and share knowledge—you make the people around you better
Automation and reproducibility are always front of mind
What You Will Do:
Design, develop, and validate statistical models and machine learning solutions that generate derivative data elements and insights for the EMEA sales intelligence platform
Work across diverse data sources—including operator, menu, concept, and market data—to identify signals, build features, and produce modelled outputs that enrich our core datasets
Own the full modelling lifecycle: problem framing, data exploration, feature engineering, model selection, validation, iteration, and operationalisation
Collaborate with the data pipeline team to integrate model outputs into production Alteryx workflows, ensuring reliable, repeatable delivery of scored and derived data
Apply current ML and AI techniques appropriately—including where LLM-based approaches can augment traditional modelling—while maintaining rigorous statistical standards
Leverage Datassential's broad-based and longitudinal foodservice dataset to build models that benefit from historical depth and evolve as new data is acquired
Translate complex modelling outputs into clear, actionable insights for internal stakeholders and, where appropriate, for customer-facing intelligence products
Contribute to the development of reusable modelling frameworks and standards that can be applied consistently across EMEA data products
Provide technical guidance to other data scientists on the team, supporting their growth in modelling rigour and best practice
Collaborate with Sales, Product, and Client teams to understand the intelligence needs of EMEA customers and translate them into modelling priorities
Stay current with relevant advances in ML, AI, and statistical methodology—and make grounded judgements about when new approaches are worth adopting
Document model design decisions, assumptions, validation results, and known limitations in a way that supports maintainability and auditability
Work with global data science colleagues to ensure EMEA modelling approaches are consistent with and complementary to the broader platform
What You Bring:
5+ years of experience in data science, quantitative modelling, or a closely related role, with a track record of taking models from development to production
Strong proficiency in Python for data science work: data manipulation, feature engineering, model development, and validation (pandas, scikit-learn, and equivalent libraries)
Strong SQL skills across one or more environments
Demonstrated command of statistical fundamentals: regression, classification, clustering, time-series analysis, hypothesis testing, and model evaluation
Hands-on experience with modern ML techniques and the judgement to select the right approach for a given problem
Experience operationalising models—not just building them—including handoff into production data pipelines
Familiarity with LLM-based approaches and where they complement or augment traditional modelling
Ability to communicate model logic, assumptions, and outputs clearly to both technical and non-technical audiences
Experience working with longitudinal or time-series datasets where historical depth is a modelling asset
Minimum of BA/BS in a quantitative field (Statistics, Mathematics, Computer Science, Economics, or equivalent); advanced degree preferred
Ability to work effectively across time zones in a remote-first, globally distributed team
Nice To Have:
Domain experience in foodservice, food & beverage, hospitality, or adjacent consumer industries
Experience with geospatial modelling or market-level aggregation and scoring
Familiarity with Alteryx or other low-code ETL environments and how model outputs are integrated into pipeline-based delivery
Experience building or contributing to sales intelligence, lead scoring, or market segmentation products
Familiarity with experiment design and A/B testing frameworks
Familiarity with project management tools such as Jira/Confluence
Our Table Welcomes All. We embrace diversity of both background and thought and foster an inclusive environment that extends an open landscape of opportunities to everyone. We invite each of us to simply be ourselves. We operate with respect and without judgment, celebrating both the power of the individual as well as our shared humanity.
If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please contact careers@datassential.com