At a Glance
- Tasks: Transform complex data into actionable insights to shape workforce strategy.
- Company: Join LSEG, a global leader in financial markets and data services.
- Benefits: Enjoy competitive pay, comprehensive benefits, and career growth opportunities.
- Other info: Collaborative culture with a focus on diversity and continuous learning.
- Why this job: Make a real impact on workforce decisions using cutting-edge analytical solutions.
- Qualifications: Experience in data science, strong Python and SQL skills required.
The predicted salary is between 63000 - 77000 £ per year.
ABOUT US
LSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open-access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It's how we've contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years. Through a comprehensive suite of trusted financial market infrastructure services - and our open-access model - we provide the flexibility, stability and trust that enable our customers to pursue their ambitions with confidence and clarity.
LSEG is headquartered in the United Kingdom, with significant operations in 70 countries across EMEA, North America, Latin America and Asia Pacific. We employ 25,000 people globally, more than half located in Asia Pacific.
OUR PEOPLE
People are at the heart of what we do and drive the success of our business. Our culture of connecting, creating opportunity and delivering excellence shape how we think, how we do things and how we help our people fulfil their potential. We embrace diversity and actively seek to attract individuals with unique backgrounds and perspectives. We break down barriers and encourage teamwork, enabling innovation and rapid development of solutions that make a difference. Our workplace generates an enriching and rewarding experience for our people and customers alike. Our vision is to build an inclusive culture in which everyone feels encouraged to fulfil their potential.
We know that real personal growth cannot be achieved by simply climbing a career ladder - which is why we encourage and enable a wealth of avenues and interesting opportunities for everyone to broaden and deepen their skills and expertise. As a global organisation spanning 70 countries and one rooted in a culture of growth, opportunity, diversity and innovation, LSEG is a place where everyone can grow, develop and fulfil your potential with meaningful careers.
ROLE SUMMARY
Are you an experienced data scientist with a passion for building practical analytical solutions and turning complex data into meaningful insight? Do you want to help shape workforce strategy in a rapidly changing environment, exploring how AI, changing demand and new ways of working affect the capabilities and capacity Engineering needs? If so, we'd love to talk to you!
ROLE OVERVIEW
As an individual contributor Lead Data Scientist within Workforce Strategy (WFS), you will take ownership of analytical projects that help Engineering understand and respond to its changing workforce needs. Working with WFS leadership and cross-functional partners, you will turn agreed business questions into practical analytical solutions, scenario models and evidence-based insights that inform workforce decisions. Your analysis will cover workforce size and shape, skills and capabilities, location and sourcing, and the implications of AI for work, productivity and capacity.
We are looking for an applied data scientist who can turn evolving business questions into focused analysis, connect complex datasets, test hypotheses and develop reusable tools, models and visualisations. The emphasis is on practical problem-solving and decision support, rather than building and operating production AI systems.
The successful candidate will combine strong technical judgement with curiosity, adaptability and a collaborative approach, working with Engineering, Finance, HR and Procurement to explain findings, make uncertainty visible and inform workforce choices.
WHAT YOU'LL BE DOING
- Translate workforce questions into analytical approaches and build reusable solutions, including exploratory notebooks, scenario models and visualisations, to investigate capacity, role mix, skills, location, sourcing and cost.
- Connect and analyse workforce, financial, planning and delivery data to establish baselines, identify trends and dependencies, and test hypotheses. Develop scenarios and sensitivity analysis that make assumptions, trade-offs and uncertainty explicit.
- Investigate how AI and automation are changing activities, skills and capacity across developer and non-developer work. Distinguish adoption from measurable changes in output, speed, quality or capacity, without assuming that usage demonstrates productivity or workforce impact.
- Apply and help improve consistent analytical methods, definitions and validation, working with data owners to resolve differences and explain limitations. Understand source structures and data flows, document lineage, reconcile differences and make data gaps, limitations and alternative explanations visible.
- Work with WFS leadership and business and technical partners to agree analytical priorities based on decision value and evidence availability, then take ownership of delivering the analysis. Iterate solutions as needs change and communicate clear findings, strategic implications and options to senior stakeholders.
WHAT YOU'LL BRING
Essential Skills:
- Bachelor's degree in Engineering, Computer Science, Data Science, Statistics, Mathematics, Physics or related field, or equivalent work experience.
- Demonstrable experience independently delivering data science projects that address complex business questions, building practical analytical solutions and translating findings into useful insight and decision support.
- Strong exploratory data analysis and statistical skills, including hypothesis testing, segmentation, trend analysis and scenario modelling; sound judgement in interpreting uncertainty, distinguishing correlation from causation and selecting methods appropriate to the evidence.
- Strong Python and SQL skills for preparing, connecting and analysing complex datasets, and developing statistical models, scenarios and clear visualisations. Ability to make analysis repeatable and adaptable as business questions change.
- Ability to work across complex enterprise datasets, understand how data is structured and flows between systems, and address inconsistent definitions, classifications and reporting periods without obscuring underlying differences.
- A rigorous approach to analytical quality, including checking data and results, documenting methods and assumptions, and ensuring findings can be reproduced and explained, with appropriate handling of confidential workforce data.
- Excellent communication and stakeholder skills, with the ability to frame business questions, explain complex findings to non-technical audiences and manage analytical priorities in a rapidly changing environment.
Desirable skills:
- Experience in workforce analytics, strategic workforce planning or organisational analysis.
- Familiarity with skills, demand and capacity modelling, and assessing AI-related changes in productivity.
- Familiarity with business intelligence tools and enterprise data platforms, and experience maintaining shared analytical work, tracking changes and checking the accuracy and consistency of analysis.
WHAT YOU'LL GET IN RETURN
- High-impact projects: Build analytical solutions and insights that help Engineering understand its workforce, explore future scenarios and make informed choices as technology and business needs evolve.
- Competitive benefits: You will enjoy a strong compensation package, comprehensive benefits, and ongoing investment in career growth and skill development.
- Contribute to an evolving capability: Help improve WFS's analytical tools, methods and evidence base through practical delivery, bringing data science to questions about the future of work, skills and capacity.
- Collaborative environment: We provide opportunities for continuous learning and professional development in a work environment of dedicated, highly experienced teams.
Career Stage: Manager
LSEG unlocks the power of markets to create opportunities across the global economy. Through our connected network of market infrastructure, data and analytics, we help customers access capital, manage risk and make confident decisions. Our insights bring clarity to complex markets, and our trusted services ensure resilience and stability. With deep expertise and global scale, we partner with customers to drive innovation and shape the future of finance.
Few organisations operate at the scale, complexity and reach of LSEG. Here, you'll work alongside experts, be inspired to deliver your best work and help shape what's next for our business and the global economy.
Guided by our values of Integrity, Partnership, Excellence and Change, we bring together diverse perspectives, encourage fresh thinking, and create an environment where learning never stops.
Join more than 26,000 colleagues across 60 countries, supporting customers in over 170 countries. Alongside flexible ways of working, you'll have access to benefits that support your wellbeing and your future, including 26 weeks' parental leave, healthcare, retirement planning and a wellness allowance. Through the LSEG Foundation and two paid volunteering days each year, you'll also have opportunities to get involved in your local community and support causes that matter to you.
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.
Data Scientist CTOO employer: LSEG
LSEG is an exceptional employer that fosters a culture of integrity, partnership, and excellence, making it an ideal place for professionals seeking to make a meaningful impact in technology procurement. With a focus on employee growth, you will have the opportunity to lead high-value negotiations and develop a talented team while working in a dynamic environment in London, where innovation and continuous improvement are at the forefront. Join us to shape the future of Corporate Engineering technology and enjoy the benefits of a supportive workplace that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist CTOO
✨Get Involved in Data Science Meetups
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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 LSEG.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist CTOO 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 Scientist CTOO
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.