At a Glance
- Tasks: Lead data science teams to create innovative AI solutions for financial services.
- Company: Join Capco, a dynamic consulting firm focused on data innovation.
- Benefits: Enjoy competitive pay, flexible holidays, and extensive training opportunities.
- Other info: Be part of a diverse culture that celebrates creativity and collaboration.
- Why this job: Make a real impact by driving data transformation in top-tier financial institutions.
- Qualifications: Experience in leading data science projects and strong Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
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.
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.
- Collaborate with business and technology teams to align technical outcomes with strategic goals.
- Provide thought leadership and best practices across the data science lifecycle, from exploration to deployment.
- Mentor and develop data professionals, fostering a culture of innovation and excellence.
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, and model governance.
- 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.
We offer a competitive, people‑first benefits package designed to support every aspect of your life:
- 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‑your growth, your way. 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.
Data Science Manager in London employer: Stryker Corporation
Stryker Corporation is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a remote setting while being part of a leading medical communications team. With a strong emphasis on professional development and growth opportunities, employees are encouraged to enhance their skills and advance their careers, all while contributing to meaningful projects that impact healthcare globally.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager in London
✨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 Stryker Corporation!
✨Show Off Your Projects
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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 Stryker Corporation.
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We think you need these skills to ace Data Science Manager in London
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 Stryker Corporation, 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 Stryker Corporation. 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 Stryker Corporation
✨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 Stryker Corporation!
✨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.
