At a Glance
- Tasks: Build and improve demand forecasting models using Python and SQL.
- Company: Join Naked Wines, a leading UK wine club with a passion for quality.
- Benefits: Competitive salary, 26 days holiday, and a supportive work environment.
- Why this job: Make an impact in the wine industry while developing your data science skills.
- Qualifications: Degree in Mathematics or Data Science with experience in demand forecasting.
- Other info: Flexible working options and opportunities for personal and professional growth.
The predicted salary is between 40000 - 50000 £ per year.
This range is provided by Naked Wines. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
In a nutshell, we’re all about making the world of wine a better place. We fund and source directly from independent winemakers to bring customers better quality wine for a better price. No thirsty middlemen as far as the eye can see. It’s a different way of doing things, sure. But it works. We’re one of the UK’s favourite wine clubs, shipping over 1 million cases a year to curious wine lovers. And with an ambitious road ahead, we’ve got no plans on plugging the cork on growth.
Our global team (we have offices in the US and Australia, too) is entrepreneurial by nature, obsessive about customer experience and driven by performance. All things that make Naked a great place to grow both personally and professionally. And yes, we like wine. A lot.
It takes a village to be Naked and now we’re looking for a Data Scientist to support and develop our demand forecasting capability across our product portfolio. You’ll work alongside experienced colleagues to build, maintain, and improve forecasting models that inform planning, commercial decisions, and S&OP processes within a D2C ecommerce environment. This role is suited to someone with strong statistical foundations who is looking to deepen their experience in demand forecasting and applied machine learning.
Together, we’ll take Naked Wines to the next level - and share our not-so-well-kept secret with the world.
Location & Flexible Working
London Office/Hybrid.
What you’ll do
- Build, maintain, and improve demand forecasting models across product segments using Python and SQL, with support from senior team members.
- Apply statistical forecasting techniques including time-series models, regression methods, and introductory machine learning approaches.
- Support scenario modelling to assess the impact of promotions, pricing changes, seasonality, and uncertainty.
- Analyse demand drivers such as customer behaviour, seasonality, pricing, and commercial activity to improve forecast accuracy and robustness.
- Validate and monitor model performance to ensure outputs are accurate, reliable, and appropriate for use.
- Track and report on forecasting KPIs including accuracy, bias, and demand variability, supporting root-cause analysis where forecasts differ from actuals.
- Contribute to forecasting for new product and wine launches, using historical analogues and early performance indicators.
- Work collaboratively with stakeholders across Sales, Marketing, Supply, Finance, Category, Logistics, and Operations to translate business context into analytical inputs.
- Prepare and communicate forecast outputs, risks, and opportunities for S&OP discussions, ensuring insights are clear, evidence-based, and actionable.
- Partner with Platform Engineering and Data Engineering to support production data pipelines and model deployment.
- Take part in the wider Analytics & Data community, sharing learnings and contributing to improvements in team practices.
What you’ll bring
- Either: A Bachelor’s degree in Mathematics, Statistics, or a related field with 2–3 years’ experience in a D2C ecommerce environment, or A Master’s degree in Data Science with 1–2 years’ relevant industry experience.
- Experience building or supporting demand forecasting models, with a solid understanding of seasonality, trend analysis, and decomposition.
- Familiarity with forecasting and machine learning approaches such as Prophet, ARIMA, and Gradient Boosting (e.g. XGBoost).
- Strong Python and SQL skills, including libraries such as Pandas, NumPy, Scikit-learn, Statsmodels, and Matplotlib.
- Experience using data visualisation tools (e.g. Looker) and applying visualisation best practices.
- Comfortable working with ambiguous or imperfect data and making informed, pragmatic decisions.
- Experience collaborating with multiple technical teams to support end-to-end data and model pipelines.
- Familiarity with Git for version control.
- Able to communicate complex ideas clearly to both technical and non-technical audiences.
You have our Naked behaviours
- Ambition (dream big): Carrying out plans effectively and actively seeking opportunities to learn.
- Judgement (make good decisions): Testing ideas and learning from outcomes; surfacing risks early.
- Discipline (adhere to high standards): Planning well and delivering high-quality work consistently and efficiently.
- Influence (have a big impact): Collaborating across teams and seeking input to widen expertise.
- Accountability (take full responsibility): Sharing honest updates and taking responsibility for outcomes.
Finally, you live by our Naked values
- You support all stakeholders from the Winemaker, through to the Customer. We are Naked Together.
- You embrace growth, pushing yourself out of your comfort zone to overcome obstacles.
- You always start with our customers and winemakers.
- You keep it simple and are data-led, from the wine itself to the ways of working.
- You do the right thing, holding yourself accountable with honesty and openness.
Recruitment Process
First Interview > Task & Task Presentation > Final Interview.
Benefits
As part of the Naked family, we want you to know we’ve got your back. Here are a few of the perks you’ll enjoy when you join the team...
A competitive salary of £40-50k pa (depending on location) plus annual bonus opportunity. 26 days holiday.
Data Scientist in London employer: Naked Wines
Contact Detail:
Naked Wines Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your demand forecasting models and any relevant projects. This is your chance to demonstrate your expertise in Python, SQL, and machine learning techniques to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your statistical foundations and forecasting techniques. Be ready to discuss how you've applied these in real-world scenarios, especially in a D2C ecommerce context.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Naked Wines family.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with demand forecasting, Python, and SQL. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data science and how you can contribute to Naked Wines. Don’t forget to mention any relevant projects or experiences that showcase your skills.
Showcase Your Technical Skills: We love seeing your technical prowess! Include specific examples of forecasting models you've built or worked on, and any tools or libraries you’re familiar with. This will help us understand your hands-on experience.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the Naked family!
How to prepare for a job interview at Naked Wines
✨Know Your Stats
Brush up on your statistical foundations and forecasting techniques. Be ready to discuss time-series models, regression methods, and machine learning approaches like ARIMA or XGBoost. Showing that you can apply these concepts practically will impress the interviewers.
✨Showcase Your Python Skills
Prepare to demonstrate your proficiency in Python and SQL. Familiarise yourself with libraries such as Pandas, NumPy, and Scikit-learn. You might be asked to solve a problem on the spot, so practice coding challenges related to data manipulation and analysis.
✨Understand the Business Context
Research Naked Wines and understand their business model. Be prepared to discuss how demand forecasting impacts their operations and customer experience. This shows that you’re not just a techie but also someone who understands the bigger picture.
✨Communicate Clearly
Practice explaining complex ideas in simple terms. You’ll need to communicate insights to both technical and non-technical stakeholders. Use examples from your past experiences where you successfully conveyed data-driven insights to diverse audiences.