Machine learning and GEN AI Data Scientist

About CITI Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. Analytics and Information Management (AIM) Citi AIM was established in 2003, and is located across multiple cities in India – Bengaluru, Chennai, Pune and Mumbai. It is a global community that objectively connects and analyzes information, to create actionable intelligence for our business leaders. It identifies fact-based opportunities for revenue growth in partnership with the businesses. The function balances customer needs, business strategy, and profit objectives using best in class and relevant analytic methodologies. What do we do? The North America Consumer Bank – Data Science and Modeling team analyzes millions of prospects and billions of customer level transactions using big data tools and machine learning, AI techniques to unlock opportunities for our clients in meeting their financial needs and create economic value for the bank. The team extracts relevant insights, identifies business opportunities, converts business problems into modeling framework, uses big data tools, latest deep learning and machine learning algorithms to build predictive models, implements solutions and designs go-to-market strategies for a huge variety of business problems. Role Description The role will be Business Analytics Analyst 2 in the Data Science and Modeling of North America Consumer Bank team The role will report to the AVP / VP leading the team What do we offer: The Next Gen Analytics (NGA) team is a part of the Analytics & Information Management (AIM) unit. The NGA modeling team will focus on the following areas of work: Role Expectations: Client Obsession – Create client centric analytic solution to business problems. Individual should be able to have a holistic view of multiple businesses and develop analytic solutions accordingly. Analytic Project Execution – Own and deliver multiple and complex analytic projects. This would require an understanding of business context, conversion of business problems in modeling, and implementing such solutions to create economic value. Domain expert – Individuals are expected to be domain expert in their sub field, as well as have a holistic view of other business lines to create better solutions. Key fields of focus are new customer acquisition, existing customer management, customer retention, product development, pricing and payment optimization and digital journey. Modeling and Tech Savvy – Always up to date with the latest use cases of modeling community, machine learning and deep learning algorithms and share knowledge within the team. Statistical mind set – Proficiency in basic statistics, hypothesis testing, segmentation and predictive modeling.