At a Glance
- Tasks: Lead data science projects and develop innovative solutions that impact millions of customers.
- Company: Join Sainsbury's, a leader in retail innovation powered by data and AI.
- Benefits: Enjoy flexible working, discounts, and a focus on personal development.
- Other info: Collaborative environment with opportunities for growth and learning.
- Why this job: Shape the future of retail with cutting-edge data science and AI technologies.
- Qualifications: Degree in a STEM field and experience in data science projects.
The predicted salary is between 60000 - 80000 £ per year.
hackajob is collaborating with Sainsbury's DTD to connect them with exceptional professionals for this role. At Sainsbury’s, data sits at the heart of how we operate, innovate and serve our customers. Our Data & Analytics team is building a technically advanced, commercially focused and impactful capability, powering our Next Level Strategy and helping to create a Sainsbury’s powered by industry leading AI algorithms. We use data, technology and advanced analytics to drive better decisions across the business, from forecasting and optimisation to experimentation, personalisation and machine learning. With one of the richest retail datasets in the UK and a portfolio spanning Sainsbury’s, Argos, Habitat and Nectar, the opportunity to innovate is huge. Here, you’ll tackle complex challenges at scale, create measurable impact and grow quickly alongside brilliant colleagues. People who thrive with us combine business understanding, technical expertise and curiosity, with a natural instinct for problem‑solving. Join us and help shape the future of retail through data and AI.
What You’ll Do
- As a Data Science Manager and a lead of one of our central Data Science teams, you will play a pivotal role in developing in‑house data science solutions that automate decision‑making and provide valuable insights across our business.
- You will lead complex data science development projects, as well as help set the direction for large‑scale ML transformation programmes.
- You will line‑manage and support several data scientists to elevate a high‑performing team.
Why join us
- Wide impact. Deploying models here means improving the experience of millions of customers each day.
- Range of projects. Our projects vary from supply chain optimisation for one of the largest logistics networks in the country, predicting which substitution products online shoppers prefer, to helping our instore colleagues keep shelves full.
- Focus on data science work. Access to extensive, clean, and well‑documented data in our industry‑leading platform: spend your time building data science solutions, not cleaning datasets.
- Time for growth. 10% of time set aside for learning & personal development.
- Learning and mentoring. With a team of 50 data scientists, engineers and product managers, there are lots of opportunities to learn from colleagues through knowledge shares, pair programming, and communities of practice.
- Flexible working. Our team prioritises hybrid working, both at home and in our central London Farringdon office.
- Save on groceries. 10% discount on products across Sainsbury's (up to 15% for two days each week).
Key Responsibilities Of The Role
- Technical leadership: Lead DS development projects as part of cross‑functional deliveries with colleagues from our allied teams: Product, Analytics, Science, and Engineering.
- Own the design and delivery of large‑scale data science solutions.
- Drive wider ML transformation programmes to support large business areas to become more data‑driven, through coordinating requirements gathering, resource allocation and managing dependencies.
- Prioritise work across complex delivery programmes and help team members prioritise the right things at the right time.
- Articulate value statements for Data Science work and produce meaningful measurement methodologies to measure business impact of your solutions.
Line management, Coaching and Team Building
- Line manage and develop our data science talent.
- Conduct code reviews and model our team’s technical standards.
- Identify opportunities for team upskilling.
- Take ownership of or lead one of our strategic initiatives: i.e. ML Ops, coding standards, training etc.
- Pair program with other data scientists.
Essential Criteria
- Educated to degree level, preferably within a mathematical, statistical or STEM discipline.
- A solid track record of individually contributing to value‑driving data science projects in a commercial setting.
- Strong proficiency with Python, SQL, and the data science stack (pandas, NumPy, scikit‑learn, etc.).
- Experience with writing production‑grade code using Python and SQL, as some of our systems involve real‑time inference that affect millions of customer transactions.
- Experience deploying models in cloud environments (Azure, AWS, GCP).
- Solid presentation skills and business acumen, you can translate an unstructured business problem into a meaningful data science project.
- Strong statistical foundation in concepts such as regression, hypothesis testing and experimental design.
- Highly proficient in Git best practices.
Desirable Experience
- Experience performing as technical lead for ML/AI projects.
- Experience building or maintaining machine learning pipelines and endpoints in Azure ML.
- Experience delivering value on ML projects in retail (in areas such as price elasticity or differential pricing) or supply chain (demand forecasting, optimisation etc.).
- Our products often utilise mathematical optimisation, so experience in this area is highly desirable.
- Experience managing data science teams, especially as part of cross‑functional programmes.
- A background in academic research in a highly numerate field.
- Deep technical knowledge in one or more data science areas: casual ML, GNNs, forecasting, optimisation, operations research, etc.
- Experience developing agentic based workflows or managing LLMs in production.
Benefits
We are committed to being a truly inclusive retailer so you’ll be welcomed whoever you are and wherever you work. Around here, there’s always the chance to try something new — whether that’s as part of an evolving team or somewhere else across the business — and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we’ll also offer you an amazing range of benefits. Here are some of them:
- Starting off with colleague discount, you'll be able to save 10% on your shopping online and instore at Sainsbury's, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year.
- We’ve also got you covered for your future with our pensions scheme and life cover.
- You'll also be able to share in our success as you may be eligible for a performance‑related bonus of up to 20% of salary, depending on how we perform.
- Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy up to an additional week's holiday, and we provide private healthcare.
- We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to £10k, cycle‑to‑work scheme, health cash plans, salary advance (where you can access some of your pay before payday) as well as access to a great range of discounts from hundreds of other retailers.
- And if you ever need it there is also an Employee Assistance Programme.
- Moments that matter are as important to us as they are to you which is why we give up to 26 weeks’ pay for maternity or adoption leave and up to 4 weeks’ pay for paternity leave.
Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibility criteria may apply).
Data Science Manager employer: hackajob
At Sainsbury's, we pride ourselves on being an exceptional employer that values innovation and collaboration within our Data & Analytics team. With a strong focus on employee growth, we offer 10% of your time for personal development, flexible hybrid working arrangements, and a supportive culture that encourages learning from talented colleagues. Our commitment to inclusivity and a range of benefits, including discounts and performance-related bonuses, makes Sainsbury's a rewarding place to build your career in data science.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like hackajob!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Manager at hackajob.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like hackajob.
✨Apply Directly through Our Website
When you find a suitable opening like Data Science Manager at hackajob, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at hackajob, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at hackajob. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at hackajob
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at hackajob!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.