Senior Data Scientist - Hybrid, London

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.

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.

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.

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.

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.