Data Science Manager

jlp; Bracknell; On-site; GBP 62,000 - 85,000; Full time

Job summary

John Lewis Partnership is seeking a Data Scientist focused on Commercial, Retail and Supply Chain to drive insight-driven decisions. You will work with stakeholders across domains, solving problems with data science techniques, building models and deploying solutions that improve customer experience and profitability.

The role sits in a central Data Science team supporting John Lewis, Waitrose and John Lewis Money, with hybrid work from Bracknell Head Office and occasional travel to other

Qualifications

• Proficient in data science with Python and SQL.
• Experience with ML Ops and Vertex AI, Git and engineering best practices.
• Strong problem-solving and collaboration skills.

Responsibilities

• Analyse complex data to support actionable insights for Commercial, Retail and Supply Chain.
• Develop and deploy data science solutions and models end-to-end.
• Collaborate with Senior Data Scientists, ML Engineers, Analysts and Architects to drive product delivery.
• Communicate benefits and use cases of AI to diverse audiences.
• Build roadmaps with stakeholders and manage project delivery.

Skills

Python

SQL

Mentoring

ML Ops

Vertex AI

Git

AI adoption

Tools

Snowflake

DBT

GitLab

Job description

ABOUT THE ROLE

The core of this role is to help the Partnership make insight-driven, better informed, customer-centric decisions specifically in our Commercial, Retail and Supply Chain domains.

In order to do this, you will need to work closely with teams across these domains in the Partnership, getting close to their world, hearing their problems and spotting the opportunities to make improvements. You will use your analytical mindset and knowledge of the customer to improve the speed and quality of decision making.

A Data Scientist focused on the Commercial, Retail and Supply Chain domains would typically solve problems such as Demand Forecasting, Price Optimisation and a range of other Constrained Optimisation tasks such as optimising markdowns to reduce food waste or setting the optimal safety stock in Distribution Centres. This role sits within a central Data Science team that covers John Lewis, Waitrose and John Lewis Money.

We are looking for someone who is passionate about solving these types of business problems across a broad spectrum of techniques that extend far and wide across consumer facing touchpoints that drive real impact in day to day situations. The successful applicant will play a hands‑on role in shaping, building and deploying business solutions alongside stakeholders and other Data Scientists and ML Engineers.

At a glance

• Hybrid working: This is a hybrid working role, therefore your time will primarily be split between working from home and Bracknell Head Office. However, there will also be an expectation to visit other locations as the need arises.


• Our team currently works from the office once a week to connect and on a more ad-hoc basis to attend key meetings, but again the frequency is dependent on the business needs.


• Expected Salary - £62,000 - £85,000 (depending upon experience)


• Contract type - This position is a permanent role.

Key Responsibilities

You will be self‑motivated and be able to work effectively together with a range of stakeholders to improve business decision making using data science methods.

You will be accountable for our roadmap and deliverables within an assigned business domain within Commercial, Retail and Supply Chain. This will also mean managing the associated stakeholders and team members within that domain.

• Analyse and link complex data sets so that they can support actionable insight and recommendations.


• Identify ideas and take ownership of opportunities to drive business impact with data science.


• Transform data and build models to optimise customer experience, profit revenue generation, cost reduction and other business outcomes.


• Be passionate about statistics and machine learning, and AI. Be able to convey a thorough understanding of the benefits and use cases of these across the business to a variety of audiences.


• Design and develop end‑to‑end solutions to business problems, from defining the problem, through solution development, to implementation and driving business adoption.


• Embrace agile working practices, set technical best practices, and actively invest in applying AI tools to enhance productivity and workflow efficiency.


• Partner with multidisciplinary agile teams-including Senior Data Scientists, ML Engineers, Analysts, and Architects-to drive technical product delivery.

Internally this role is known as Insight Manager, Data Science.

Essential Skills and Experience

• Hands-on Expertise: Proficient in data science, with coding experience in Python and SQL, and the ability to mentor others.


• Technical Proficiency: Experience with ML Ops (Vertex AI), Git version control and software engineering best practices whilst using AI effectively to augment these best practices.


• Problem-Solving and Innovation: A passion for tackling business challenges and applying new data science techniques.


• Communication and Collaboration: Excellent communication skills, experience working in cross‑functional teams, and the ability to build data science roadmaps with stakeholders.


• Business Acumen: Adept at working with stakeholders to identify and prioritise key problems, and optimise against KPIs to achieve their objectives.


• AI & Learning Mindset : Passion for continuous learning, with a desire to apply AI tools effectively to optimise day‑to‑day work processes.

Desirable Skills and Experience

• Work experience within the Retail or Grocery sectors.


• Hands‑on experience with Agile methodologies in multidisciplinary product teams.


• Experience applying software engineering best practices (e.g., modern tech stack usage like Snowflake, DBT, GitLab).


• Experience working with Cloud technologies (specifically Google Cloud Platform)


• Previous people management experience.

Next Steps

The application form consists of a CV upload, followed by application questions. Please save the application questions to a document file (such as Google Docs, Word or Notepad) before entering on Workday.

Once you've submitted an application the next s