Company Overview :

REFINITIV INDIA SHARED SERVICES PRIVATE LIMITED is a critical hub within the global Refinitiv organization, a leading provider of financial markets data and infrastructure. We empower the world's financial community with data, analytics, and trading solutions, serving professionals across investment banking, asset management, wealth management, and corporate sectors. Our Bangalore center plays a pivotal role in developing and delivering innovative technology solutions, driving product development, and supporting global operations, contributing significantly to the platforms that power financial markets worldwide.

Role Overview :

As a Senior Data Scientist, you will be instrumental in leveraging advanced analytical techniques and machine learning to extract actionable insights from vast and complex financial datasets. This role involves end-to-end ownership of data science projects, from problem definition and data exploration to model development, deployment, and monitoring. You will collaborate closely with product managers, engineers, and business stakeholders across various global teams to translate business challenges into data-driven solutions, directly impacting product innovation, operational efficiency, and strategic decision-making for our clients and internal operations.

Key Responsibilities :

- Design and implement robust machine learning models and algorithms to solve complex business problems for financial market applications.

- Lead the full lifecycle of data science projects, including data acquisition, cleaning, feature engineering, model training, validation, and deployment into production environments.

- Collaborate with engineering teams to integrate models into existing platforms and build scalable data pipelines on cloud infrastructure.

- Conduct in-depth exploratory data analysis to identify trends, patterns, and anomalies, providing strategic recommendations to product and business units.

- Mentor junior data scientists, fostering a culture of continuous learning and best practices in data science methodologies.

- Present findings and technical concepts clearly and concisely to both technical and non-technical audiences, influencing key stakeholders.

Required Skillset :

- Demonstrated expertise in developing and deploying machine learning and artificial intelligence (AIML) solutions, with a strong portfolio of projects.

- Proficient in Python and R for data manipulation, statistical analysis, and machine learning model development.

- Extensive experience with Large Language Models (LLM) and natural language processing techniques, including fine-tuning and application development.

- Solid understanding and practical experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage, processing, and model deployment.

- Advanced SQL skills for querying and manipulating large datasets, along with experience in data warehousing concepts.

- Proven ability to translate complex business problems into data science solutions, demonstrating strong analytical and problem-solving capabilities.

- Excellent communication and interpersonal skills, with a track record of effective collaboration with cross-functional teams and presenting technical insights to diverse audiences.

- A minimum of 5- 8 years of progressive experience in data science roles, preferably within the financial services or a related data-intensive industry.

- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.