Data Science II-SUPPORT SERVICES-Data & Analytics - In House Engineering

Job Title : Data Scientist 2
Location :Bangalore
About Kotak Mahindra Group:
Established in 1985, the Kotak Mahindra Group is one of India’s leading financial services conglomerates. In February 2003, Kotak Mahindra Finance Ltd (KMFL), the group’s flagship company, received a banking license from the Reserve Bank of India (RBI). With this, KMFL became the first non-banking finance company in India to become a bank – Kotak Mahindra Bank Limited.
The Group offers a wide range of financial services that encompass every sphere of life. From commercial banking, to stock broking, mutual funds, life insurance and investment banking, the Group caters to the diverse financial needs of individuals and the corporate sector. The Group has a wide distribution network through branches and franchisees across India, the international offices in London, New York, California, Dubai, Abu Dhabi, Bahrain, Mauritius and Singapore. For information, please visit the company’s website at
http://www.kotak.com
Why Join Us?
Opportunity to work with an established leader in the banking industry
Exposure to cutting-edge analytics and business strategy in the rapidly evolving credit card sector
Collaborative inclusive work culture with a focus on professional development and growth
Analyze large datasets related , customer behavior, transaction trends, and operational performance.
Interpret complex data and provide actionable insights to business stakeholders for decision making.
Collaborate with senior management to understand business objectives and deliver data drive insights to support strategic initiatives.
Assist in the development of business cases for new credit card products, marketing strategies and customer acquisition programs.
Conduct ad-hoc analysis and scenario modeling to evaluate the impact of potential business changes or initiatives.
Support the optimization of portfolio by identifying opportunities for product enhancements, risk mitigation, and customer segmentation.
Work closely with risk, marketing, finance, and operations teams to align on data, models, and strategies.
Ensure accuracy, integrity, and consistency of data used for analytics and reporting.
Collaborate with IT and data management teams to improve data infrastructure and data governance practices.
Automate processes to ensure scalability of solutions by collaborating with cross-functional teams.
Bachelors/Masters in a quantitative field (Engineering, Statistics, Econometrics, Mathematics, Operations Research, Computer Science etc).
3-5- years of experience in Data Science
Strong programming background (Python, Pyspark, SAS, SQL etc.) with proficiency in Microsoft Office suite. Experience in financial modeling is an added advantage.
Proven track record of working with large datasets. Experience in data visualization tools such as Power BI is an added advantage.
Understanding of credit card product structures, risk models, and portfolio management techniques.
Strong quantitative skills with the ability to analyze complex datasets, derive insights, and present findings to non-technical stakeholders.
Ability to develop and deliver actionable recommendations to drive business improvements.
Excellent communication skills with the ability to convey complex data insights in a clear and concise manner.
Strong interpersonal skills and the ability to work effectively in a cross-functional, team-oriented environment.
Familiarity with ML models - XGBoost, Light GBM, Random Forests, SVMs, multivariate analysis, clustering, dimensionality reduction is an added advantage.
Experience in carrying out data processing including statistical analysis, variable selection, and dimensionality reduction, custom feature engineering, as well as the evaluation of new alternate data sources.
Experience in partnering with business teams to implement strategies in production.
Job Description:
We are seeking a highly motivated and detail-oriented Data Science to join our Team.
Roles and Responsibilities:
Skill requirements:

Work arrangement
No