Data Science Manager

Capco is hiring a Data Science Manager in London, United Kingdom. Level rates it ; you can apply on Capco.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include MLOps and AI safety.
Level lists 702 other open roles at Capco.

AI in this role

ml-opsai-safety

Data Science Manager

Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent

Shape intelligent solutions. Lead with insight. Drive data innovation.

The Role

We’re looking for a Data Science Manager to lead innovative projects that apply data, AI, and machine learning to solve complex challenges across financial services. You’ll guide talented data professionals, collaborate closely with business stakeholders, and drive impactful, scalable solutions that deliver measurable business value. You'll champion AI-enabled ways of working, encouraging the responsible use of approved AI tools and automations to improve delivery quality, productivity, and insight while maintaining appropriate human oversight and governance.

What You’ll Do

Lead data science teams to design, develop, and deploy advanced machine learning and AI solutions.
Drive the adoption of cutting-edge technologies including generative AI, LLMs, and agentic AI frameworks, while promoting responsible AI practices, governance, and appropriate human review throughout the delivery lifecycle.
Collaborate with business and technology teams to align technical outcomes with strategic goals, leveraging AI-enabled workflows where appropriate to accelerate insight and delivery.
Provide thought leadership and best practices across the data science lifecycle, from exploration to deployment, including scalable MLOps, model governance, and responsible AI implementation.
Mentor and develop data professionals, fostering a culture of innovation, continuous learning.

What We’re Looking For

Proven experience leading the delivery of data science or AI projects from concept to production.
Strong knowledge of Python and core ML libraries (e.g., spaCy, NumPy, SciPy, Transformers).
Understanding of big data and cloud technologies (Spark, Hadoop, Azure, AWS, or GCP).
Deep expertise in MLOps principles, scalable model deployment, model governance, and the practical application of responsible AI within enterprise environments.
Excellent communication and stakeholder management skills with the ability to translate data insights into business value.

Bonus Points For

MSc or PhD in a numerate discipline.
Experience in Banking or Financial Services.
Exposure to GenAI, LLMs, and intelligent agent workflows.
Experience with DevOps, CI/CD, and productionising ML systems.
A passion for mentoring and developing early-career data talent,

Why Join Capco

Deliver innovative, high-impact data solutions for Tier 1 financial institutions.
Work in a collaborative, entrepreneurial consulting environment.
Access continuous learning, training, and industry certifications.
Join a growing global Data Practice of 800+ experts driving transformation.
Be part of a culture where individuality, creativity, and collaboration are celebrated.

Benefits

Core Benefits: Discretionary bonus, competitive pension, health insurance, life insurance and critical illness cover.
Mental Health: Easy access to CareFirst, Unmind, Aviva consultations, and in-house first aiders.
Family-Friendly: Maternity, adoption, shared parental leave, plus paid leave for sickness, pregnancy loss, fertility treatment, menopause, and bereavement.
Family Care: 8 complimentary backup care sessions for emergency childcare or elder care.
Holiday Flexibility: 5 weeks of annual leave with the option to buy or sell holiday days based on your needs.
Continuous Learning: Minimum 40 hours of training annually- choose workshops, certifications, or e-learning. Business Coach assigned from Day One for one-on-one guidance.
Healthcare Access: Convenient online GP services.
Extra Perks: Gympass (Wellhub), travel insurance, Tastecard, season ticket loans, Cycle to Work, and dental insurance.

Inclusion at Capco

We’re committed to a barrier-free, inclusive recruitment process. If you need any adjustments at any stage, just let us know- we’ll be happy to help. We welcome applicants from all backgrounds. At Capco, we value the difference you make, and the differences that make you. Our #BeYourselfAtWork culture champions diversity, equity, and inclusion, and we bring a collaborative mindset to everything we do.

#LI-DNI

How we rate this

Data Science Manager at Capco rates 82 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Science Manager is an open job at Capco.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in UK - London.
The job was posted on October 29, 2025.
Applications are handled by Capco. Apply on Capco

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI Safety

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: ML Ops and AI Safety. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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