LSEG Junior Data Scientist Bangalore freshers 0-3 years experience apply now Full Time

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.

Role, Responsibilities & Key Accountabilities:

• Contribute to the development of data acquisition, cleaning, 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 experts 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 best practices.
• Stay current 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, adopting 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 with the ability to explain technical concepts clearly.
• Ability to collaborate across teams, take feedback, and contribute to 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.
• Experience 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.

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