Stott and May
Lead Product Data Scientist

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Job Description
Lead Product Data Scientist
Hybrid - West London - 3 Days Min
AI, Machine Learning & Optimisation
Our client is seeking a Lead Product Data Scientist to lead the delivery of AI, machine learning and optimisation solutions within a complex operational environment.
You'll combine hands-on technical expertise with team leadership, working closely with stakeholders, engineers and product teams to build data-driven products that improve decision-making and deliver measurable business value.
Key Responsibilities
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
- Lead the development of ML, optimisation and decision-support products.
- Define technical strategy, product roadmaps and delivery plans.
- Manage and mentor data scientists and engineers.
- Translate business challenges into scalable analytical solutions.
- Drive product adoption, stakeholder engagement and value realisation.
- Ensure best practices across software engineering, deployment and support.
Experience Required
- Strong experience in machine learning, optimisation and applied data science.
- Advanced Python skills and experience delivering production-grade solutions.
- Background leading technical teams and stakeholder engagement.
- Knowledge of cloud platforms, data pipelines and modern software development practices.
- Experience within logistics, transport, aviation, retail, manufacturing or other operationally intensive industries is desirable.


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Opportunity for a senior technical leader with a proven track record of delivering impactful AI and optimisation products at scale.
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