Senior Data Scientist

Overview

Senior Data Scientist in the Emerging Tech Standard Delivery Team, driving adoption of advanced technologies and building enterprise-ready solutions for D&A Operations, partnering with Operations and Technology teams.

What you'll do

• Own the product vision for an industry-leading data management framework covering data acquisition, cleaning, transformation and related workflows.
• Support the Lead Data Scientist on the end-to-end AI/ML lifecycle: problem definition, design, experimentation, deployment and continuous improvement.
• Define an optimized user experience for financial analytics data pipelines, unifying multiple tools and services into an integrated workflow.
• Partner with analytics domain experts to translate business data needs into a practical platform and framework strategy.
• Lead execution of this strategy in close collaboration with engineering and project delivery teams.
• Communicate product goals, progress and achievements to product, engineering, business leaders, sales, proposition, support and other internal stakeholders.
• Stay informed on financial analytics market trends to maintain a forward-looking, future-ready strategy.
• Continuously learn and adapt to emerging technologies and techniques in financial analytics.
• Develop and deploy production-grade AI models and data-driven solutions aligned with strategic objectives.
• Tune and optimize AI models to improve accuracy, performance and scalability.
• Evaluate third-party AI capabilities using both functional and non-functional criteria.
• Establish and enforce coding standards to ensure a maintainable, robust codebase.
• Collaborate with Software Engineers and cross-functional teams to define requirements, set direction and shape development roadmaps.
• Design and implement evaluation frameworks for automation solutions based on business requirements.
• Build solutions and onboard workloads on AWS or other cloud platforms.
• Apply web crawling and scraping techniques, entity identification and extraction, and advanced pre- and post-processing methods, including prompt engineering.
• Process structured, semi-structured and unstructured data from PDFs and scanned documents.

What you'll need

• 6-8 years of experience in data science, analytics or statistical modelling roles.
• Strong foundation in data analytics, feature engineering, NLP, predictive modelling, LLMs and RAG workflows.
• Hands-on experience in NLP, Large Language Models, prompt engineering and Retrieval-Augmented Generation (RAG).
• Skilled in training, testing and validating deep learning and classical machine learning models.
• Expertise in Python and core ML/DL libraries (TensorFlow, PyTorch, Scikit-learn), with demonstrated experience developing and productionizing AI models.
• Proven ability to apply strong statistical analysis skills, including probability and applied statistics, to model development and evaluation.
• Experience with Git-based version control and CI/CD pipelines (GitLab/GitHub runners).
• Strong understanding of relational databases, large-scale data processing and statistical programming.
• Familiarity with MLOps principles and experience deploying solutions on cloud platforms (AWS and/or Azure).
• Hands-on experience with leading commercial or open-source data management tools.
• Ability to diagnose and resolve complex technical and business problems using deep analytical and industry knowledge.
• Ability to set and uphold coding standards.
• Excellent written, verbal and presentation skills, able to simplify complex technical concepts for technical and business audiences.
• Strong influencing and collaboration skills, supporting cross-team execution and alignment.
• Broad business awareness and understanding of relevant internal business relationships.
• Proficiency in Python, R and SQL.
• 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.

Nice to have

• Experience in large financial services or investment banking environments.
• Familiarity with Refinitiv or LSEG products and financial data workflows.
• Experience working with global or distributed teams.
• Comfort interacting with senior stakeholders, including executives and C-suite partners.

Details

• Location: Bangalore, India (Tower E, RMZ Infin).
• Career stage: Senior Associate.