About us:
YuLife is an award-winning InsurTech company and an employee benefit provider.
We’re the world’s first “lifestyle insurance” company. While other insurers are there for people at the point of death or illness, we engage with people every day to help them live better lives.
To do that, we’ve built an award-winning app that rewards people for building healthy habits. It includes the best wellbeing and digital health tools in the world.
Customers can earn vouchers from great brands like Amazon, Tesco or ASOS for doing simple things like walking or practicing mindfulness. They can even do good by planting trees or cleaning the oceans from the app.
Our clients include Tesco, Capital One and Fujitsu, and we’ve been ranked the #1 employee benefit in the UK on Trustpilot. More recently, YuLife was recognized by CX Insurance Awards as ‘Best Insurtech 2024’ and the 8th Fastest Growing Technology Company in the UK in the prestigious 2023 Deloitte Technology Fast 50.
The role:
At YuLife, we’re on a mission to inspire life and help people be their best selves every day. As a Data Scientist, you will play a critical role in building smart, scalable data solutions that enhance our customer relationships, optimise sales strategies, and improve user engagement through data-driven insights and automation.
You'll work closely with cross-functional teams including Sales, Marketing, Product, Customer Success, and Engineering to develop and maintain robust predictive models, internal tools, and intelligent systems. You’ll be empowered to own end-to-end data science initiatives from hypothesis to production; with the aim of making a tangible impact on how we engage with and support our users.
We’re looking for someone who is not just technically excellent, but also commercially curious, creative, and eager to solve meaningful problems.
Key Responsibilities
Customer Behaviour Modelling: Build and evaluate predictive models for churn, engagement, and customer lifetime value, with a focus on interpretability and business impact.
Academic-style Research & Modelling: Conduct exploratory research and develop novel modelling approaches grounded in statistical theory and scientific literature to solve complex business problems and support innovation.
Sales & Marketing Insights: Analyse customer and prospect data to uncover trends, segment audiences, and support personalisation in marketing and sales campaigns.
Internal Consulting: Serve as an embedded data partner for cross-functional teams, helping frame and solve high-impact business questions with data.
Experimentation & Uplift Modelling: Design and analyse A/B tests and experiments to measure the impact of new features, campaigns, or interventions.
Anomaly & Trend Detection: Monitor key customer metrics and develop tools to detect deviations or emerging patterns that require business attention.
Data Storytelling & Communication: Build compelling dashboards and reports that clearly communicate findings to both technical and non-technical stakeholders.
Tooling & Workflow Improvement: Create reusable notebooks and lightweight tools that make it easier for teams to access and understand data.
Technical Skills
Languages & Tools:
Python (Pandas, NumPy, Scikit-learn, Statsmodels)
SQL for data extraction and transformation
Data visualisation with Tableau, Plotly, or Matplotlib
Jupyter Notebooks and version control with Git
Analytical & Modelling Expertise:
Predictive modelling (logistic regression, tree-based models, time series)
Customer segmentation (clustering, RFM analysis)
Statistical testing, A/B testing, and experimental design
Strong foundation in statistics, data wrangling, and feature engineering
Collaboration & Communication:
Proven ability to explain complex analyses to non-technical audiences
Experience working cross-functionally in product, marketing, or sales contexts
Clear documentation and presentation of findings and methodologies
Preferred but not essential:
Familiarity with data platforms like Snowflake or BigQuery
Exposure to MLOps tools (e.g. MLFlow) for collaborative model tracking
Knowledge of marketing analytics, lifecycle modelling, or CRM systems
Minimum Qualifications
Master’s degree in a quantitative field (e.g. Statistics, Mathematics, Data Science, or related discipline)
3+ years of experience applying data science in a commercial environment
Demonstrated ability to work independently on end-to-end data projects
Strong problem-solving skills and intellectual curiosity
Excellent communication and collaboration skills
What you’ll get:
We like to give more than we take so here are some of our benefits:
- Competitive base salary
- Potential to earn share options
- 6x salary life assurance
- Health Insurance
- Income protection
- 3% company contribution to pension via salary sacrifice scheme
- 25 days Annual Leave + 1 Love being Yu (e.g your birthday, moving house anything else that is for Yu!)
Additional Perks:
- Access to the YuLife app (which includes a tonne of well-being rewards, discounts and exclusive offers as well as access to Meditopia and Fiit)
- £20 per month to a "be your best Yu" budget
- Unlimited Monthly professional coaching with More Happi
- OnHand Volunteering app
- Learning Budget
- Financial coaching with Octopus Money
- Generous parental leave
- Remote working package; includes laptop, desk, chair etc.
- Remote and flexible working
- Currently our lovely office in Shoreditch is available if people want (and only if they want) to use it
Our framework and principles around hybrid working at YuLife.
Here at YuLife our values encompasses Love Being Yu and as a result we’re committed to diversity and inclusion. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, colour, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, disability or any other protected class.
Read what one of our key investors has to say about our culture ›
We're more than just life insurance!
