Principal Data Scientist - Artificial Intelligence/Machine Learning - BFSI

Job Title : Principal Data Scientist/AI/ML COE

Experience :

• 18-25 years of total relevant experience.

• Minimum of 4 years in leadership roles in Artificial Intelligence & Machine Learning (AI/ML)

• Deep experience in building end to end AI/ML based applications along with big data technologies

• Expertise in machine learning, statistical modelling, and data mining techniques.

• Proficiency in Python, R, or similar programming languages, and experience with big data tools (e.g., Spark, Hadoop).

• Deep understanding of AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Knowledge of cloud platforms (OpenShift, AWS, GCP) and MLOps pipelines.

• Experience with data visualization tools (e.g., Power BI) to communicate insights effectively.

• Experience with natural language processing (NLP) and computer vision.

• Familiarity with data privacy regulations and ethical AI practices.

Key Responsibilities :

He/she will be a techno managerial leadership role responsible for leading a top-class data team, providing technical vision, analytical support and business intelligence, to analyse large amount of raw information to find patterns, build data products and models to extract valuable business insights. He/she is expected to manage a team and contribute :

• Develop and implement the ReBIT's data science strategy in alignment with RBI / Central banking business objectives.

• Identify opportunities for AI/ML and advanced analytics to solve business challenges and improve processes.

• Provide thought leadership on leveraging data science and machine learning for competitive advantage.

• Oversee the design, development, and deployment of predictive and prescriptive models, recommendation systems, and other AI/ML applications.

• Implement cutting-edge techniques, such as deep learning, natural language processing (NLP), and computer vision, to address complex problems.

• Ensure scalable model development and deployment through MLOps practices.

• Build, lead, and mentor a team of data scientists, analysts, and engineers to deliver high-quality solutions.

• Collaborate with cross-functional teams (e.g., Product, IT, Finance) to identify business opportunities and translate them into data science projects.

• Effectively communicate complex data-driven insights to both technical and non-technical audiences, including senior executives.

• Ensure timely delivery of data science projects, meeting scope, budget, and quality standards.