Roles & Responsibilities:
- Analyse complex data sets to extract insights and identify trends.
- Develop predictive models and algorithms to solve business problems.
- Work on deployment of models in production.
- Collaborate with cross-functional teams to understand requirements and deliver data-driven solutions.
- Clean, preprocess, and manipulate data for analysis through programming.
- Communicate findings and recommendations to stakeholders through reports and presentations.
- Stay updated with industry trends and best practices in data science.
- Contribute to the development and improvement of data infrastructure and processes.
- Design experiments and statistical analysis to validate hypotheses and improve models.
- Continuously learn and enhance skills in data science techniques and tools.
- Strongly support the adoption of data science across the organization.
- Identify problems in the products, services and operations of the bank and solve those with innovative research driven solutions.
Essential Skills:
- Strong hands-on programming experience in Python (mandatory), R, SQL, Hive and Spark.
- More than 3 years of relevant experience.
- Ability to write well designed, modular and optimized code.
- Knowledge of H2O.ai, GitHub, Big Data and ML Engineering.
- Knowledge of commonly used data structures and algorithms.
- Good to have: Knowledge of Time Series, NLP and Deep Learning and Generative AI is preferred.
- Good to have: Knowledge and hands-on experience in developing solutions with Large Language Models.
- Must have been part of projects building and deploying predictive models in production (financial services domain preferred) involving large and complex data sets.
- Strong problem solving and critical thinking skills.
- Curious, fast learning capability and team player attitude is a must.
- Ability to communicate clearly and effectively.
- Demonstrated expertise through blogposts, research, participation in competitions, speaking opportunities, patents and paper publications.
- Most importantly - ability to identify and translate theories into real applications to solve practical problems.
Preferred Skills:
- Good to have: Knowledge and hands-on data engineering or model deployment
- Experience in Data Science in either of Credit Risk, Pricing Modelling and Monitoring, , Sales and Marketing, Campaign Analytics, Ecommerce Retail or banking products for retail or business banking is preferred.
- Solid foundation of Statistics and core ML algorithms at a mathematical (under the hood) level.
Education Qualifications : Bachelor’s degree in Engineering in Computer Science/Information Technology.