Data Science Manager

Data Science Manager

Full-Time 75600 - 92400 £ / year (est.) Home office (partial)
LSEG

At a Glance

  • Tasks: Lead a team to build innovative AI solutions for financial markets.
  • Company: Join a leading global financial markets infrastructure provider.
  • Benefits: Enjoy competitive pay, healthcare, and opportunities for professional growth.
  • Other info: Be part of a diverse team that values innovation and collaboration.
  • Why this job: Shape the future of AI while making a real impact in finance.
  • Qualifications: Proven leadership in AI/ML and experience with large-scale projects.

The predicted salary is between 75600 - 92400 £ per year.

Are you an experienced Data Science leader with a passion for building and scaling AI/ML products?

Lead a team of exceptional Data Scientists and ML Engineers building next-generation AI solutions for financial markets. Drive innovation using

LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, and advanced Machine Learning to deliver real-world business impact.

If you're passionate about shaping the future of AI, we'd love to talk to you.

Role Summary

As a

Data Science Manager , you will lead a high-performing team of Data Scientists delivering AI-powered products that create measurable business value at scale.

This role combines technical leadership, people leadership, and strategic execution .

You will drive innovation in AI and Machine Learning, establish engineering excellence, and develop exceptional talent while delivering production-grade solutions that solve complex customer problems.

The ideal candidate has a consistent track record of leading technical teams, scaling AI initiatives from concept to production, and fostering a culture of innovation, collaboration, and continuous improvement.

You will partner closely with Product, Engineering, Research, and business partners to shape strategy, accelerate execution, and deliver impactful AI solutions.

What You'll Be Doing

This role combines technical leadership, organizational leadership, and strategic execution within a high-impact AI organization.

  • Technical Leadership
  • Lead the design, development, evaluation, and deployment of production-grade AI and Machine Learning solutions.
  • Drive innovation in Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Deep Learning, and Transformer-based architectures.
  • Define the technical vision for AI products, ensuring solutions are scalable, secure, maintainable, and aligned with business objectives.
  • Provide deep expertise in model development, experimentation, optimization, evaluation, and production deployment.
  • Establish standard methodologies for LLM evaluation, model benchmarking, AI quality measurement, and performance assessment.
  • Evaluate emerging AI technologies, foundation models, and third-party solutions to find opportunities for innovation and business value.
  • Guide architectural decisions across AI platforms, model-serving infrastructure, data pipelines, and MLOps/LLMOps capabilities.
  • Partner closely with Engineering teams to productionize AI solutions and drive operational excellence.
  • Build, mentor, and lead high-performing teams of Data Scientists and AI/ML practitioners.
  • Set clear goals, drive accountability, and support career growth and development.
  • Lead performance management, coaching, feedback, and talent development activities.
  • Foster a culture of innovation, collaboration, ownership, and continuous learning.
  • Drive hiring, onboarding, succession planning, and team growth initiatives.
  • Accelerate technical excellence through mentoring, technical reviews, and knowledge sharing.
  • Strategic & Delivery Leadership
  • Partner with Product, Engineering, and Business leaders to define AI strategy, roadmap, and priorities.
  • Drive execution through effective planning, prioritization, resource management, and delivery oversight.
  • Deliver high-quality AI solutions that create measurable business value.
  • Champion engineering excellence through guidelines, coding standards, experimentation, and governance.
  • Communicate technical strategy, risks, and recommendations clearly to technical and executive collaborators.
  • Promote responsible AI, model governance, compliance, and operational risk management.
  • What You'll Bring

ESSENTIAL SKILLS

  • LEADERSHIP & MANAGEMENT
  • Proven track record of building, leading, and developing high-performing teams of Data Scientists, ML Engineers, and AI practitioners.
  • Demonstrated success delivering large-scale AI initiatives from ideation to production with measurable business impact.
  • Strong coaching, mentoring, performance management, and talent development capabilities.
  • Experience leading multiple concurrent programs, balancing priorities, resources, and customer expectations.
  • Exceptional leadership, communication, and influencing skills with experience engaging senior leadership and executive collaborators.
  • TECHNICAL EXPERTISE
  • Extensive experience designing, building, and deploying production-grade AI and Machine Learning solutions at scale.
  • Deep expertise in LLMs, Generative AI, RAG, Agentic AI, Deep Learning, Neural Networks, and Transformer architectures.
  • Hands-on experience with LLM evaluation, benchmark design, model validation, prompt engineering, guardrails, and AI quality assessment.
  • Good foundation in statistics, probability, optimization, experimentation, and applied machine learning.
  • Advanced proficiency in Python and modern AI frameworks, including Py Torch, Tensor Flow, Scikit-Learn, Hugging Face, Lang Chain, Semantic Kernel, and related ecosystems.
  • Experience building and scaling enterprise AI platforms, ML infrastructure, and intelligent applications serving thousands of users.
  • Strong understanding of model observability, monitoring, evaluation frameworks, experimentation, reliability, and operational perfection.
  • Expertise in cloud-native AI development using Azure AI Foundry, Azure Machine Learning, Azure Open AI, Azure AI Search, AWS AI Services, and modern cloud architectures.
  • Experience implementing MLOps and LLMOps practices, including CI/CD, model lifecycle management, governance, and production operations at scale.
  • COLLABORATION & COMMUNICATION
  • Ability to communicate complex technical concepts clearly to technical, business, and executive audiences.
  • Strong interested party leadership skills with a proven track record to drive alignment across Product, Engineering, Research, and Business teams.
  • Known to work influencing technical strategy, product direction, and organizational decision-making.

Desirable Skills

  • Experience leading teams building AI products for financial services, capital markets, research, analytics, or other data-intensive domains.
  • Experience developing multi-agent systems, autonomous workflows, copilots, and intelligent AI assistants.
  • Knowledge of reinforcement learning, fine-tuning, synthetic data generation, model compression, and advanced optimization techniques.
  • Experience with Knowledge Graphs, vector databases, semantic search, retrieval systems, and Graph RAG architectures.
  • Strong understanding of Responsible AI, model governance, AI safety, privacy, regulatory compliance, and risk management frameworks.
  • Experience with Dev Ops, CI/CD, Kubernetes, Infrastructure as Code, containerization, and distributed computing platforms.
  • Contributions to the AI community through publications, patents, conference presentations, research, or open-source projects.

EDUCATION

Bachelor's degree or equivalent experience in

Computer Science, Data Science, Statistics, Mathematics, Engineering, Physics, Artificial Intelligence, Machine Learning , or a related quantitative field.

Master's Or Equivalent Experience Or Ph D Preferred.

  • WHAT YOU’LL GET IN RETURN
  • HIGH-IMPACT AI LEADERSHIP

Lead the development of next-generation AI products , demonstrating large-scale datasets, advanced AI models, and modern technologies to solve complex customer challenges.

SIGNIFICANT OWNERSHIP

Shape AI strategy, influence product direction, and build capabilities that deliver dynamic outcomes for customers worldwide.

  • INDUSTRY LEADERSHIP
  • Work at the forefront of

Generative AI, LLMs, Agentic AI, Analytics, and Intelligent Search , helping define the future of AI innovation in financial markets.

CAREER GROWTH

Accelerate your leadership and technical career through continuous learning, innovation, and exposure to large-scale AI initiatives.

WE ARE PROUD OF OUR VALUES

We recognize that attracting exceptional talent requires flexibility and inclusivity.

We take a hybrid-first approach and are committed to creating an environment where different perspectives, continuous learning, and innovation can thrive.

We encourage applications from individuals of all backgrounds and experiences and are committed to providing equal opportunities for all.

Career Stage

Manager

London Stock Exchange Group (LSEG) Information

Join us and be part of a team that values innovation, quality, and continuous improvement.

If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.

LSEG is a leading global financial markets infrastructure and data provider.

Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

  • Our purpose is the foundation on which our culture is built. Our values of
  • Integrity, Partnership ,
  • Excellence and

Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries.

However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

We are proud to be an equal opportunities employer.

This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law.

Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas.

We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives.

Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence.

Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.

If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.

#J-18808-Ljbffr

Data Science Manager employer: LSEG

LSEG is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about AI and technology. With a strong emphasis on employee growth, we offer numerous opportunities for professional development and collaboration on cutting-edge projects in a hybrid work environment. Join us in London to be part of a forward-thinking team that values creativity and technical expertise, making a meaningful impact in the world of finance and technology.

LSEG

Contact Details:

LSEG Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Science Manager

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 LSEG!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Manager at LSEG.

Leverage Professional Networks

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 LSEG.

Apply Directly through Our Website

When you find a suitable opening like Data Science Manager at LSEG, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Science Manager

Leadership
Team Development
AI Product Development
Machine Learning Solutions
Generative AI
Large Language Models (LLMs)
Deep Learning

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 LSEG, 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 LSEG. 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 LSEG

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 LSEG!

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.