Junior Data Scientist

About the role

The Emerging Tech Standard Delivery Team is looking for a Junior Data Scientist to help design data‑driven solutions that create measurable business and customer value. You will work closely with Operations and Technology groups, learning financial content and core D&A processes while applying the latest analytics, NLP, and deep‑learning techniques.

Key responsibilities

• Develop data acquisition, normalization, transformation, and processing workflows within the enterprise data management framework.
• Support design and improvement of financial analytics pipelines, integrating tools for seamless end‑to‑end user experiences.
• Translate analytics requirements into clear tasks, models, or pipeline components under senior guidance.
• Collaborate with engineering, product, and delivery teams to implement data solutions.
• Build and evaluate machine‑learning and deep‑learning models, including NLP, LLMs, and RAG‑based approaches.
• Create evaluation frameworks to measure automation and AI effectiveness.
• Perform data processing tasks such as web scraping, entity extraction, and pre/post‑processing of structured and unstructured documents.
• Support cloud‑based development (AWS or similar) and follow CI/CD and MLOps guidelines.

Required profile

• 0–3 years of experience in data science, analytics, or statistical modelling (including internships or academic projects).
• Foundational knowledge of feature engineering, machine learning, NLP, LLMs, and RAG workflows.
• Strong analytical thinking and problem‑solving abilities.
• Ability to work with large datasets, perform data cleaning, transformation, and exploratory analysis.

Required skills

• Python programming
• Pandas, NumPy, Scikit‑learn libraries
• Git version control and CI/CD pipelines (GitLab/GitHub runners)
• Relational databases and basic statistical concepts
• Cloud platforms (AWS or Azure) and MLOps fundamentals
• NLP, LLM, RAG techniques
• Web scraping and entity extraction
• Synthetic data generation concepts