Lead data scientist Work, Jobs in Enderby, Lec (with Salaries)

Lead Data Scientist
NEXT —Leicester
- From £66,000 a year
- Full-time
- Computer Science
- Mentoring
- AI
- Free parking
- Employee discount
11d

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Lead Data Scientist

NEXT -
Leicester

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Job details

Full-time
From £66,000 a year
11 days ago

Benefits

Free parking
Discounted gym membership
Private medical insurance
Employee discount
On-site parking

Qualifications

CI/CD
Law
Computer Science
Mentoring junior staff
Mathematics
E-commerce
CI/CD pipelines
Machine learning modelling
Deep learning
Mentoring
A/B testing
Data science
AI
Project leadership
Communication skills

Full job description

We are looking for a Lead Data Scientist to join the eCommerce Data team with a competitive salary range starting from £66,000 alongside great benefits, such as company profit related bonus, private medical insurance, staff discount and more! Based from Next Head Office in Enderby, Leicestershire.

The Role:

eCommerce Data drives the department and the business profitability and growth by powering live trade, merchandising and personalised experiences.

As a Lead Data Scientist at NEXT, you will take ownership of data science solutions end to end - framing the problem, designing the solution and building it into production in front of millions of customers across a catalogue of millions of products and 70+ markets. This is a hands-on, build it yourself role: you write the production code. You will work with state of the art machine learning, including deep learning and modern LLM and agent based systems and prove real impact through rigorous evaluation and experimentation. As a lead, you set the technical direction on your projects, are accountable for the delivery, how it performs and mentor other data scientists.

What You’ll Take On:

You will partner with the business, working closely with product, engineering, trading and merchandising teams to understand challenges and opportunities in eCommerce.
Proactively lead the design, development and deployment of ML/AI solutions - owning the architecture, the trade offs and the delivery plan, writing the design documents the team builds from and mentoring juniors.
Build machine learning solutions across search, recommendations and personalisation, including training and fine tuning deep learning models where they genuinely beat the simpler option: sequence transformers, two tower retrieval, neural and gradient boosted LTR, multimodal image and text embeddings etc.
Build LLM and agentic applications - retrieval grounded, tool using, constrained - with the evaluation harnesses that decide whether they are good enough to ship and keep them honest once they have.
Deliver and maintain containerised training and inference, orchestrated ML pipelines, feature and model registries, model serving, drift monitoring, retraining and rollback.
Design and run experiments that settle the question - clear hypotheses, agreed guardrails and honest readouts, including the ones that say the model did not win.
Set the standards for data quality, model governance, evaluation and documentation, and raise the bar through design and code review.

What You’ll Bring:

Significant experience in applied data science or machine learning with a degree in computer science, mathematics, or related field.
A track record of owning solutions end to end and shipping models that moved a business metric.
Strong expertise in advanced statistics, machine learning, deep learning and hands-on experience with training and fine-tuning large models.
Excellent Python, SQL, PySpark, Pytorch/Tensorflow and git experience with production grade software engineering discipline - code standards, version control, testing, code review, and documentation.
Practical experience building and evaluating LLM and agentic systems — RAG, tool use, orchestration frameworks such as LangGraph, and offline and online evals for non-deterministic systems.
Experienced designing and running A/B tests and other forms of experimental design. Causal inference, off policy evaluation and bandits are nice to have.
Strong communication skills with the ability to translate complex data insights into actionable business strategies, and to explain a modelling trade-off to a non-technical audience.
Experience/exposure to Docker, K8s, CI/CD and react/ next.js , Triton, vLLM etc is a plus.

You do not need to tick every single requirement but a drive to learn and develop is important.

25% off most NEXT, MADE*, Lipsy*, Gap* and Victoria's Secret* products (*when purchased through NEXT)
Company performance based bonus
Sharesave scheme
On-site Nursery available; OFSTED outstanding in all areas
10% off most partner brands & up to 15% off Branded Beauty
Early VIP access to sale stock
Access to fantastic discounts at our Staff Shops
Restaurants with great food at amazing prices
Access a digital GP and other free health and wellbeing services
Free on-site parking
Financial Wellbeing - Save, track and enhance your financial wellbeing
Apprenticeship - Grow and develop on the job whilst gaining a qualification
Direct to Work - Discount online and instore, collect your items the next day for free from your place of work or local store
Support Networks - Access to Network Groups to empower and celebrate each other

Conditions apply to all benefits. These benefits are discretionary and subject to change.

We aim to support all candidates during the application process and are happy to provide workplace adjustments when necessary. Should you need support with your application due to a disability or long-term condition, feel free to get in touch with us by email [email protected] (please include 'Workplace Adjustments' in the subject line), or call us on 0116 284 2486 and leave a voicemail.

You know Next, but did you know we’re a FTSE-100 retail company employing over 44,000 people across the Next group. We’re the UK’s 2nd largest fashion retailer and for Kidswear we’re the market leader. At the last count we have over 450 stores, plus the Next Online and it’s now possible to buy on-line from over 80 countries around the world! So we’ve gone global!

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