Specialized Analytics Senior Analyst - Assistant Vice President

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Job Overview

The Specialized Analytics Sr Anlst is a seasoned professional role.

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), Langgraph, Langchain frameworks 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:

Responsibilities:

Lead the architecture, design, and development of mission-critical, production-grade Generative AI applications and Agentic solutions, ensuring they are scalable, reliable, and secure.

Define and own the technical roadmap for AI platforms, making critical decisions on architecture, technology stacks, and long-term evolution.

Drive the strategy for designing and redesigning business processes with Agentic solutions, focusing on advanced agent architecture, memory management, hallucination control, and reinforcement learning-based feedback loops.

Champion and enforce best practices for compliance, security, MLOps, and Model Governance across all AI projects.

Engage with senior stakeholders to translate business needs into technical strategy and communicate technical vision and project status.

Stay at the forefront of AI research and industry trends, identifying new opportunities and technologies to drive business value.

Responsibilities:

Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies

Identifies and compiles data sets using a variety of tools (e.g. SQL, Access) to help predict, improve, and measure the success of key business to business outcomes

Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / 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

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.

Recommended Qualifications:

10+ years of experience

Must have the ability to retrieve and manipulation data

Advanced analytic ability and problem solving skills to proactively address business questions with innovative data driven solutions

Ability to build partnerships with cross-functional teams in order

Working experience in a quantitative field, Financial/Credit Card industry

Willing to learn and can-do attitude

Excellent communication and interpersonal skills, be organized, detail oriented, flexible and adaptive to matrix work environment

Education:

Bachelor's/University degree; Master's degree highly preferred in Computer Science, AI, Engineering, or a related quantitative field.

Technical Proficiency:

Hands-on experience in applied machine learning, Generative AI solutions (e.g., Prompt Engineering, Retrieval Augmented Generation (RAG), Google ADK, Langgraph, Langchain frameworks and Big Data technologies.

Proficiency in scripting languages (e.g., Python) 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.

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

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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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