AVP Specialized Analytics

Description The role will be AVP - Specialized Analytics Sr Anlst in the Data Science and Modeling of North America Consumer Bank team The role will report to the VP/ SVP 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 – As an SME, 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. Communication skills – Ability to translate and articulate technical thoughts and ideas to a larger audience including influencing skills with peers and senior management. Strong project management skills. Ability to coach and mentor juniors . Contribute to organizational initiatives in wide ranging areas including competency development, training, organizational building activities etc. Role Responsibilities: Incumbents are required to work with large and complex data sets using a variety of tools (Python, PySpark, SQL, R etc.) to build optimization/modeling solutions for various business requirements Primary focus areas would be Model building, model validations, model implementation and model governance related responsibilities for multiple portfolios Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis, which may include utilizing statistical models / optimization algorithms and data visualization techniques Incumbents in this role may often be referred to as Data Scientists Specialization in marketing, risk, digital and AML fields possible The analyst will work with other members in the team and business partners to jointly build model driven solutions using traditional methods (Linear, Logistic, Segmentation etc.) as well Machine Learning driven modeling solutions Work with model governance & fair lending teams to ensure compliance of models in accordance with Citi standards Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency Basic qualifications: Master’s with 7+ years of professional experience in fields that include but not exhaustive – Computer Science, Machine Learning, Operations Research, Econometrics, Statistics or in a highly quantitative field. Technical SkillsSound knowledge of machine learning/deep learning and statistical modeling techniques.Experience working with Machine Learning software frameworks and relevant Python libraries , scikit-learn, xgboost, Keras, NLTK, BERT, TensorFlow etc.,Hands-on experience in PySpark/Python/R programing along with strong experience in SQL.Experience working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and background in Statistical Analysis. Self-motivated and able to implement innovative solutions at fast pace Structured thought process to identify, clearly articulate and solve complex problems and present them to the management in a structured and simpler form Experience in Credit Cards and Retail Banking is preferred CompetenciesStrong communication skillsMultiple stake holder managementStrong analytical and problem solving skillsExcellent written and oral communication skillsStrong team playerControl orientated and Risk awarenessWorking experience in a quantitative fieldWilling to learn and can-do attitudeAbility to build partnerships with cross-function leaders Preferred qualifications: Experience working on Transformers/ LLMs (OpenAI, Claude, Gemini etc.,), Prompt engineering, RAG based architectures and relevant tools/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, LangChain/Graph, LlamaIndex etc., Understanding of transformers/language models Familiarity with vector databases and fine-tuning techniques Education: Bachelor's / Master degree in Economics / Statistics / Mathematics / Information Technology / Computer Applications / Engineering etc. from a premier institute Other Details Employment: Full Time Industry: Credit Cards, Retail Banking, Financial Services, Banking ------------------------------------------------------ Job Family Group: Decision Management------------------------------------------------------ Job Family: Specialized Analytics (Data Science/Computational Statistics)------------------------------------------------------ Time Type: ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above.------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------