Job Description
ZOE is a science and nutrition company dedicated to improving health through scientifically proven solutions. As a Data Scientist, you will collaborate with nutrition scientists to develop scoring algorithms, build ML/AI models using member data to enhance user experience and health outcomes, and engineer bespoke models incorporating expert knowledge. This role involves rigorous validation on real-world data and shipping production-ready code. You will work within cross-functional teams, prioritizing intellectual honesty and rapid experimentation. Responsibilities include designing and deploying scoring algorithms, translating scientific findings into model features, building robust Python code, and developing ML/AI models for various applications. The ideal candidate has 3+ years of experience in data science or related fields, a strong foundation in machine learning and statistical techniques, and experience with production-level Python and SQL. Passion for nutrition, health tech, or biology is highly valued.
Good To Have:
- Experience with causal inference
- Experience with advanced statistical modeling
- Experience building AI features using LLMs
- Exposure to MLOps best practices
- Knowledge of microbiome data or biomarker analytics
Must Have:
- 3+ years of experience in data science or ML engineering
- Solid grasp of machine learning and statistics
- Experience with production-level Python codebases
- SQL query experience
- Git for version control
- Turning domain knowledge into model logic
- Shipped production code
- Excellent communication and collaboration skills
- Passion for nutrition, health tech, or biology
- Commitment to rapid iteration with imperfect data
Perks:
- Competitive compensation package including base pay and stock options
- Comprehensive benefits including health insurance and wellness programs
- Inclusive parental policies
- Tailored professional development programs
- Support for personal and professional growth
We Are Redefining How People Approach Their Health
ZOE is the science and nutrition company leading a movement to transform the health of millions.
We exist because the food we eat is making us sick. Most of what we are taught about food is wrong.
ZOE runs the world’s largest nutrition science study to find scientifically proven solutions.
Our randomised controlled trial of ZOE proves that if you eat the right food for your body, you can feel healthier in weeks and be on track for more healthy years.
ZOE can change the way you eat, feel, and live. We host world-leading scientists on our podcast and bring proven science to your plate with Daily30+, our 30+ plant supplement.
Over 100,000 people rely on ZOE Membership, our personalised nutrition program, to make smarter food choices. ZOE Membership turns complex science into clear step-by-step actions, helping you improve your health with every meal.
ZOE means life — and you can change your life with food.
Visit our career page and become a ZOEntist 🚀
🚀 The Role
As a Data Scientist at ZOE, you will partner with world-class nutrition scientists to turn cutting-edge research into robust scoring algorithms and science-driven features, and to build ML/AI models that leverage our extensive members’ data to improve user experience and health outcomes.
This role is perfect for someone passionate about nutrition, health tech, or biology, or someone with the curiosity and drive to dive in and learn quickly.
Unlike a classical “fit-the-model” data science role, you’ll also engineer bespoke models that embed expert knowledge, validate them rigorously on real-world data, and ship production-ready code that powers the ZOE experience. You’ll collaborate daily with scientists, engineers, and product teams—moving fast and iterating quickly based on strong but not perfect evidence (~70 %) because speed beats perfection in a startup.
👥 The Team
You’ll be joining the Data Science team at Zoe. The team spends most of its time embedded in stream-aligned product teams while regularly setting aside a smaller portion of its schedule to drive high-impact, cross-cutting data science initiatives for the wider organisation.
Your home base will be the Scoring team—a cross-functional team of product managers, engineers, scientists, and data scientists that sits at the nexus of research and product. You’ll join a squad that prizes intellectual honesty, rapid experimentation, and our #ActFast ethos—working hand-in-hand with PhD scientists to turn hypotheses into deployed models.
🎯 What You’ll Be Doing
- Design, iterate, and deploy scoring algorithms for foods, diets, metabolic responses, and microbiome profiles.
- Translate expert food statements (e.g., ‘High-glycaemic foods raise blood glucose responses’) into model features and Python functions.
- Build, test, and maintain clean, production-ready code in Python (pandas, NumPy, scikit-learn), and SQL/DBT/BigQuery/Airflow.
- Build ML/AI models to improve food coverage and categorisation, ingredients extraction, food recommendations, and more.
- Design validation frameworks that blend scientific rigour (e.g., hold-out tests, bootstrapping, sensitivity analyses) with pragmatic speed.
- Partner with engineers to shape data contracts and ensure pipelines deliver the granularity, latency, and quality your models require.
- Present results using decks, dashboards, or Looms to support data-driven product decisions.
- Take full ownership of your work, brining entrepreneurial spirit and work proactively.
- Champion our scientific yet agile approach: start with a hypothesis, seek evidence, and iterate fast.
🧠 What You’ll Bring to the Table
- 3+ years of professional experience in data science, ML engineering, or quantitative research.
- A degree in a quantitative field (e.g., Applied Maths, Physics, Biomedical Engineering, Statistics, Computer Science).
- Solid grasp of machine learning (e.g. training and evaluating standard models) and statistical techniques (e.g. running hypothesis testing).
- Experienced in contributing to production-level Python codebases, developing new components and features, writing moderately complex SQL queries, and using Git for version control.
- Experience turning domain knowledge (rules, heuristics, scientific findings) into engineered model logic.
- A track record of shipping production code and collaborating in cross-functional, fast-paced environments.
- Comfort using AI tools to enhance day-to-day productivity—from IDEs with AI assistants to prompt engineering.
- Strong communication and collaboration skills—from delivering clear presentations to stakeholders to conducting deep-dive code reviews and working collaboratively across functions.
- Must have a passion for nutrition, health tech, biology, or a strong desire to dive in and learn quickly.
- A commitment to our #ActFast value: optimise for reversible decisions, take smart risks, and move quickly with imperfect data.
🌟 Bonus Points
- Experience with causal inference and advanced statistical modelling.
- Experience with building AI features using LLMs and evaluation frameworks.
- Exposure to MLOps best practices.
- Knowledge of microbiome data, ---omics pipelines, or biomarker analytics.
✨ Our Hiring Journey
- 👋 Stage 1: Talent Screening Interview – 30 mins – With Laia, Talent Acquisition Manager
- 💡 Stage 2: Hiring Manager Interview – 45 mins – With Joan or Francesca, Data Science Leads
- 🧪 Stage 3: Final Round Interviews
- 🎉 Offer
A first conversation to learn more about your background, motivations, and interest in joining ZOE. We'll also give you an overview of the role, team, and what to expect from the process.
A deeper dive into your experience, technical strengths, and areas of interest. We’ll explore the impact of your previous work, how you approach problem-solving, and what excites you about data science at ZOE.
Technical Interview – 60 mins
An interactive session to assess your data science skills. You might walk us through past work, discuss a technical challenge, or solve a problem live — it’s all about understanding how you think and approach real-world problems.
Cross-Functional Interview – 45 mins
You’ll meet team members from other disciplines (like product, engineering, or nutrition science). We want to see how you collaborate across teams and communicate complex ideas in a clear, accessible way.
Leadership & Behavioural Interview –45 mins
A behavioural-style interview focusing on how you lead projects (with or without a formal title), work under pressure, handle ambiguity, and contribute to team culture. We'll also take time to answer any remaining questions you have.
If everything clicks, we’ll move to offer quickly and transparently. You'll always know where you stand and what comes next.
The experience, skills, and attributes listed above reflect what we believe will contribute to success in this role. If you're passionate about ZOE and the opportunity, but don't meet 100% of the criteria, we still encourage you to apply. We are committed to supporting growth and are happy to offer up-skilling opportunities where possible.
Remote Philosophy
ZOE is a remote-first company, meaning remote work isn’t just an option — it’s how we work best. We are intentional about building a distributed, high-performing team where collaboration, trust, and flexibility thrive.
We design our workflows around asynchronous communication and shared documentation to support autonomy, focus, and cross-timezone collaboration. While our teams work independently, connection and teamwork remain central to how we operate — through regular rituals, meaningful virtual interactions, and in-person gatherings every quarter. These include team offsites and a yearly company-wide retreat to build relationships, spark creativity, and have fun together.
Being remote-first also means we value outcomes over hours and trust our team members to manage their work in a way that suits their unique rhythm and responsibilities. This approach allows us to support a truly flexible work environment, while staying aligned with our mission and values.
At ZOE, working remotely doesn’t mean working alone — it means being empowered, supported, and connected, wherever you are.
Compensation Philosophy
We are committed to offering competitive and equitable compensation that reflects the value of each role and aligns with regional labor market standards. Our approach to compensation goes beyond just base salary — we offer a comprehensive package that includes base pay and stock options, ensuring that every team member is rewarded for their contributions to the company’s growth and success.
We believe that building a thriving team requires not only providing fair and competitive compensation but also fostering an environment where success is shared collectively. Our total compensation package is designed to support the well-being of our employees, recognise their individual contributions, and empower them to grow alongside ZOE.
Benefits & Perks
We understand the significant role our benefits play in motivating, inspiring and safeguarding our employees' well-being. Our benefits strategy is thoughtfully designed to echo our mission and values, recognising the diverse needs arising from different life stages of our ZOEntists.
Our approach to benefits takes an inclusive and flexible view of both personal and professional growth. From competitive health insurance and wellness packages to inclusive parental policies, building connection, and tailored professional development programs, we've got you covered.
At ZOE, we continue to build a benefits package that invests in our team members’ long-term personal and professional growth and wellbeing, adding to this list as it evolves.
Equal opportunities
We are committed to fostering a diverse and inclusive team where every individual can bring their authentic self to work. We believe that this is key to our success and are dedicated to positively impacting the tech industry. As part of our commitment to equal opportunities, we encourage candidates from underrepresented backgrounds to apply. We ensure a respectful and inclusive environment for all and do not discriminate on the basis of race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, marital status, disability, or age. If you require any accommodations during the interview process, please feel free to inform us, and we will make every effort to support your needs.
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