The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise‑ready solutions for D&A Operations. In this role, the individual partners with Operations and Technology teams to design data‑driven solutions that deliver clear business and customer value.
The position requires strong expertise in analytics, NLP, deep learning, and data communication, along with ability to learn financial content and core D&A business processes. The individual must know the newer technologies and collaborate operations groups and specialized machine learning teams to deliver scalable, high‑impact solutions.
Role, Responsibilities & Key Accountabilities:
- Work to the development of data acquisition, normalization, transformation, and processing workflows as part of the enterprise data management framework.
- Support the design and improvement of financial analytics data pipelines, helping integrate tools and services to create smooth, end‑to‑end user experiences.
- Work with analytics domain to understand data requirements and translate them into clear tasks, models, or pipeline components under the guidance of senior team members.
- Assist in implementing data solutions by collaborating with engineering, product, and project delivery teams.
- Participate in building and evaluating machine learning and deep learning models, including NLP, LLMs, and RAG‑based approaches.
- Help create evaluation frameworks that measure the effectiveness of automation and AI solutions.
- Carry out data processing tasks such as web scraping, entity extraction, and pre‑/post‑processing of structured, semi‑structured, and unstructured documents (e.g., PDFs, scanned files).
- Support cloud‑based development (AWS or similar), including onboarding workloads and following CI/CD and MLOps guidelines.
- Know the latest with emerging technologies, analytics techniques, and financial data trends to continually improve your skills.
Required Skills:
- 0–3 years of experience in data science, analytics, or statistical modelling (including internships or academic projects).
- Foundational knowledge in data analytics, feature engineering, ML, NLP, LLMs, and RAG workflows.
- Proficiency with Python and familiarity with core data science libraries (Pandas, NumPy, Scikit‑learn, etc.).
- Experience using Git and exposure to CI/CD pipelines (GitLab/GitHub runners).
- Understanding of relational databases, statistics, and basic statistical programming concepts.
- Ability to work with large datasets and perform data cleaning, transformation, and exploratory analysis.
- Exposure to MLOps fundamentals and experience working with cloud platforms (AWS/Azure).
- Ability to set and uphold coding standards.
- Apply AI Agents and human‑AI collaboration frameworks, embracing AI as a productivity amplifier across business functions
- Understanding Synthetic Data generation techniques to overcome real‑data scarcity, enhance model robustness, and support privacy‑preserving AI development
- Strong analytical thinking, problem‑solving ability, and prioritization skills.
- Effective communication skills and ability to explain technical concepts clearly.
- Ability to collaborate across teams, take feedback, and work on shared goals.
- Hands-on experience with leading commercial or open-source data management tools.
- Excellent written, verbal, and presentation skills, with the ability to present to peers, senior management, and cross-functional partners.
- Broad business awareness and understanding of relevant internal business relationships.
- Ability to resolve complex business challenges using deep technical knowledge and industry insight.
Preferred
- Exposure to financial services, investment banking, or related domains.
- Familiarity with Refinitiv or LSEG platforms and datasets.
- Working with distributed or global teams.
Education:
- Master’s degree in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing in Data Science and Artificial Intelligence.
- Proficiency in Python, R, and SQL.
Career Stage:
Senior Associate
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.
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