Applied Senior Data Scientist (Forecasting and Opportunity)
Applied Senior Data Scientist (Forecasting and Opportunity Analytics)
London (Hybrid), 4 days a week (Flexible)
Foresight Factory helps the world’s most ambitious organisations see further ahead. Powered by our proprietary intelligence platform, Collision, we transform fragmented data into foresight that drives decisive action. Our work sits at the intersection of data science, strategic insight, and commercial impact - deep, smart, and unapologetically future-focused.
Role Overview
As an Applied Senior Data Scientist, you will sit at the heart of how Foresight Factory turns raw data into future-shaping intelligence.
You will design, stress-test, and evolve predictive systems that identify early signals of change, anticipate emerging consumer behaviours, and reveal new growth opportunities. Your work will directly influence how global clients decide when to act, where to invest, and how to stay ahead.
You’ll operate as both a hands-on technical leader and a strategic partner - modelling forecasting approaches across complex datasets, translating noise into clarity, and ensuring our intelligence products remain genuinely future-ready.
What you’ll actually be doing
- Designing and deploying forecasting and simulation models across structured and unstructured datasets
- Identifying weak signals, inflection points, and pattern shifts in consumer and industry data
- Partnering with consultants, developers, and analysts to shape client-facing intelligence products
- Elevating internal data science standards, tooling, and modelling approaches
- Translating complex modelling outputs into strategic narratives that non-technical stakeholders can act on
Required experience
- 5+ years operating in a senior or lead data science capacity, with clear ownership of models and outcomes
- Degree-level STEM qualification (or equivalent professional experience)
- Demonstrated commercial impact through applied statistics and predictive modelling
- Experience with forecasting and probabilistic approaches, including ML techniques (e.g. SARIMA, Monte Carlo, XGBoost, ANN)
- High proficiency in Python and SQL
- Comfortable operating autonomously, making judgement calls, and navigating ambiguity
Nice to have
- Experience within a consulting or advisory environment
- Familiarity with market research and consumer insight datasets
- Experience designing production-grade data visualisations
- Working knowledge of cloud and collaboration tooling (AWS/Azure, GitHub)
Why this role?
You’ll be joining a diverse, intellectually curious team that values rigour, creativity, and responsibility in equal measure. This role offers exposure to how data science directly shapes strategic decisions, with the freedom to work creatively in influencing methods, models, and the future direction of our intelligence platform.
Flexible working patterns, a four-day week (by default*), and a genuinely people-first culture mean you can do your best thinking without burning out.
*We anticipate this being a four-day week role, but we’re open to discussing three or five days depending on the candidate. Salary will be pro-rated to reflect agreed working hours.
What you’ll get in return
- Competitive Salary commensurate with experience
- Performance-related bonus
- Workplace pension with 3% company contribution
- 2 x base salary life insurance
- Vitality healthcare insurance
- 28 days’ holiday plus public holidays
- Ability to swap existing public holidays for celebrations or holidays of other religions
- Continuous professional development linked to company objectives and personal goals
- Flexible work patterns and hybrid working
- Ability to work from anywhere in the world – 2 weeks per annum
- Family friendly and compassionate leave policies
- Great design-led (and dog-friendly) office space in the heart of Shoreditch
- Free membership to on-site gym through Manor London
- Season ticket loans, cycle to work and personal tech schemes
- Wellbeing support program
- End of quarter company celebrations and frequent team outings