Senior Data Scientist - Generative AI

The role shall bring in innovation and provide competitive advantages for the Bank.

We are looking for a candidate who has practical experience with analytics technologies and languages supporting data science domains models using machine learning and linear algorithms

- Should have worked on classification, regression, and forecasting business problem statements

- Expertise in model training and validation to improve accuracy and model stability

- Experience in maintaining analytics models and developing analytics governance frameworks

- Should have worked in different technology stacks (Cloud/on Prem) for model deployment and production

- Experience in working with business stakeholders and for curation of analytics problems

- Should have worked on banking use cases like cross-sell, upsell, customer retention, customer acquisition, customer servicing, personalization, ATM optimization, Branch analytics

- Own Data assessment for analytics and building data foundations for analytics use cases

- Exposure to Artificial intelligence techniques and use cases.

Exposure to Gen AI is a value-add

- Hands-on programming experience in Python

Job Profile :

- Join a fully functional team of enthusiastic Data Scientists and Visualization experts to solve various banking-related problem statements

- Senior Data scientist will develop and maintain statistical models, apply machine learning techniques, and build high-quality predictive/prescriptive systems

- The senior data scientist will also make technology and business recommendations, as well as develop key insights based on data analysis

- The candidate must be able to partner with business stakeholders and serve as a domain expert in order to curate business problem statements and guide business priorities using data

Skill & Competencies Requirement :

- Proficiency in predictive modeling, feature engineering, Hypothesis testing, and Machine Learning techniques (Decision Trees, GBM, XG-Boost, GLM modeling, Forecasting, Scorecard development, Clustering)

- Proficiency in A/B Testing, campaign design, and scaling data science models into production-level models that can handle complex real-time data

- Good hands-on experience in Python and SQL

- Expertise in different cloud analytics Tech-stacks (AWS/ Azure/ GCP)

- Proficiency in analytics project management and working with business Stakeholders

- Excellent communication skills with ability to explain the problems/solutions with clarity

- Must have good presentation skills

- Exposure to AWS services like Sagemaker, Glue, Athena, S3, etc