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, Gurgaon 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 Next Gen Analytics 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, implement solutions and design go-to-market strategies for a huge variety of business problems

What’s expected from you?

We are seeking an experienced analytics candidate who should be able to perform below behaviors in their day-to-day role:

• Generative AI Solution Leadership – Design, develop, and implement stable, "best-in-class" Generative AI solutions using recommended tools and frameworks. Continuously prove and improve the performance and impact of developed solutions.
• Team Leadership & Development - Lead, mentor, and manage a team of 10-15 Data Scientists, fostering their growth and ensuring high-quality output
• Strategic Business & Technical Communication – Act as a bridge between technical teams and business partners, effectively extracting and understanding business needs. Translate complex technical designs, solution capabilities, and performance metrics into clear, actionable insights for senior business audiences.
• Strategic Vision & Innovation – Demonstrate strong strategic acumen by understanding the broader business landscape, identifying emerging trends, and challenging the status quo to define ambitious goals for growth within the Generative AI space.
• Subject Matter Expertise & Knowledge Sharing – Maintain deep expertise in the latest Generative AI use cases, machine learning algorithms, deep learning techniques, and relevant public datasets. Proactively share knowledge and insights across the wider data science and engineering teams.
• Analytical & Statistical Rigor – Ensure the application of sound statistical principles, including hypothesis testing, segmentation, and advanced predictive modeling, in all solution designs and analyses.
• Risk Management & Compliance:  Appropriately assess and mitigate risks associated with Generative AI solutions, demonstrating consideration for the firm's reputation. Safeguard Citigroup, its clients, and assets by ensuring solutions comply with all applicable laws, rules, and regulations.
• Model Governance & Compliance: Collaborate closely with model governance and fair lending teams to ensure that all developed models adhere to Citi's rigorous standards and regulatory requirements

Skillset you should possess

The Senior Manager, Data Science (Generative AI) role demands a robust technical foundation, primarily in Generative AI. This includes deep expertise in Deep Learning and Machine Learning algorithms, practical experience with Generative AI technologies and frameworks, and specialized skills in Prompt Engineering, Retrieval Augmented Generation (RAG), and Large Language Model (LLM) fine-tuning. Candidates must be adept at Generative AI solution design and implementation. Complementing this, strong data science technical skills are essential, encompassing proficiency in programming languages like Python, experience with data manipulation tools such as PySpark, SQL, and Hive, and the ability to handle data requirements, collection, processing, cleaning, exploratory data analysis, and effective data visualization. A solid understanding of analytical and statistical foundations, including hypothesis testing, segmentation, predictive modeling, and performance optimization, is also crucial.

Beyond technical expertise, the role requires significant leadership and management capabilities, including the ability to lead, mentor, and develop a team of data scientists. Strategic acumen is paramount, demanding a candidate who can demonstrate strategic thinking and vision, identify emerging trends, challenge the status quo, and drive innovation to set ambitious business goals. Excellent communication and stakeholder management skills are also vital for effectively translating complex technical concepts and performance metrics for senior business audiences and ensuring strong collaboration with both team members and business partners. Apart from these, they should also have the following skillset:

Basic Qualifications

The candidate should possess a strong academic and professional background, demonstrating deep expertise in data science and Generative AI.

• Educational Background: Master’s degree in computer science, Machine Learning, Operations Research, Econometrics, Statistics, or a highly quantitative field.
• Professional Experience: 12-15 years of progressive professional experience in relevant fields.
• Technical Proficiency:
  • Hands-on experience in applied machine learning, Generative AI solutions (e.g., Prompt Engineering, Retrieval Augmented Generation (RAG), LLM fine-tuning), and Big Data technologies.
  • Proficiency in scripting languages (e.g., Python, Pyspark) and key libraries.
  • Strong expertise in deep learning and machine learning algorithms, especially those applicable to Generative AI (e.g., large language models, diffusion models), data analysis, and pattern recognition.
• Model Governance & Problem Solving:
  • Robust understanding of Model Governance, Risk, and Evaluation frameworks at both model and enterprise levels.
  • Demonstrated structured thought process to identify, articulate, and solve complex problems, translating them into clear, simplified presentations for management.
• Documentation: Excellent documentation skills, including the ability to create comprehensive design documents, methodologies, and internal content.

Preferred Qualifications

Candidates with the following additional qualifications will be highly regarded.

• Platform Experience: Experience with Big Data platforms, Cloud environments, Spark, and Hive.
• Communication: Exceptional written and oral communication skills, with a proven ability to simplify complex technical methods for non-expert audiences.

Development Tools: Experience with shell scripting, bash, and Git/GitHub for version control and collaboration.

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Job Family Group:

Decision Management

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Job Family:

Specialized Analytics (Data Science/Computational Statistics)

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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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.

 

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