Citi

Data Science Analyst(GenAI & Prompt Engineering)

New

PayCompetitive
LocationGurugram/Haryana
Employment typeFull-Time
  • Job Description

      Req#: 26943453

      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.

      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 (e.g., 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 Skills

      Hands-on experience in PySpark/Python/R programing along with strong experience in SQL.

      2-4 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 coding.

      Strong 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

      Competencies

      Strong communication skills

      Multiple stake holder management

      Strong analytical and problem solving skills

      Excellent written and oral communication skills

      Strong team player

      Control orientated and Risk awareness

      Working experience in a quantitative field

      Willing to learn and can-do attitude

      Ability 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.

      ------------------------------------------------------

      Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

      If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi .

      View Citi’s EEO Policy Statement and the Know Your Rights poster.

  • About the company

      While we're a global bank, our mission is simple: We responsibly provide financial services that enable growth and economic progress. We strive to earn and maintain the public's trust by constantly adhering to the highest ethical standards. We ask our colleagues to ensure that their decisions pass three tests: they are in our clients' interests, create economic value, and are always systemically responsible. When we do these things well, we make a positive financial and social impact in the communities we serve and show what a global bank can do.

Notice

Talentify is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

Talentify provides reasonable accommodations to qualified applicants with disabilities, including disabled veterans. Request assistance at accessibility@talentify.io or 407-000-0000.

Federal law requires every new hire to complete Form I-9 and present proof of identity and U.S. work eligibility.

An Automated Employment Decision Tool (AEDT) will score your job-related skills and responses. Bias-audit & data-use details: www.talentify.io/bias-audit-report. NYC applicants may request an alternative process or accommodation at aedt@talentify.io or 407-000-0000.