Spec Analytics Analyst

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. 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: Work with large and complex datasets using a variety of tools (Python, PySpark, SQL, Hive, etc.) and frameworks to build Deep learning/generative AI solutions for various business requirements. Primary focus areas include model training/fine-tuning, model validation, model deployment, and model governance related to multiple portfolios. Design, fine-tune and implement LLMs/GenAI applications using techniques like prompt engineering, Retrieval Augmented Generation (RAG) and model fine-tuning Responsible for documenting data requirements, data collection/processing/cleaning, and exploratory data analysis, including utilizing deep learning /generative AI 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, applying Deep learning & generative AI models  to innovate in these domains. Collaborate with team members and business partners to build model-driven solutions using cutting-edge Generative AI models (, Large Language Models) and also at times, ML/ traditional methods (XGBoost, Linear, Logistic, Segmentation, etc.) 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. What do we look for: If you are a bright and talented individual looking for a career in AI and Machine Learning with a focus on Generative AI , Citi has amazing opportunities for you. Bachelor’s Degree with atleast 3 years of experience in data analytics, or Master’s Degree with 2 years of experience in data analytics, or PhD. Technical SkillsHands-on experience in PySpark/Python/R programing along with strong experience in years of experience working on deep learning, and generative AI applications 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, LlamaIndex etc., Solid understanding of deep learning, transformers/language models .Familiarity with vector databases and fine-tuning techniques Experience working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and background in Statistical Analysis.Capability to validate/maintain deployed models in production Self-motivated and able to implement innovative solutions at fast pace 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 Education: Bachelor's / master’s 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: Full time------------------------------------------------------ Most Relevant Skills Please see the requirements listed above.------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------