Job Description Control Automation Data Science Analyst

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Job Overview

Control Automation Data Science Sr Analyst (C11) - DS

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.

About AIM:

Analytics and Information Management (AIM) is a global community that is driving data driven transformation across Citi in multiple functions with the objective to create actionable intelligence for our business leaders. We are a fast-growing organization working with Citi businesses and functions across the world.

What do we do:

We have one formula for managing risk across the firm: our Enterprise Risk Management Framework. This consistency enables us to take an end-to-end view in how we identify, measure, build, control and report risks. We are also working to simplify, streamline and automate our manual controls - strengthening our ability to prevent issues, not just to detect them after they happen. When issues do appear, we should strive to understand the root cause. We can then apply those lessons-learned horizontally across the organization to prevent similar issues from arising elsewhere.

Expertise required:

AI Solution Development: Design, develop, and implement AI-powered solutions using large language models (LLMs) and other machine learning techniques to address business challenges and opportunities.

Prompt Engineering: Create, refine, and optimize prompts to guide LLMs and other generative AI tools, ensuring accurate, relevant, and high-quality outputs for a variety of applications.

Tool Utilization: Effectively use AI-powered tools like GitHub Copilot and other industry-available platforms to accelerate development, automate tasks, and improve overall productivity.

Collaboration and Integration: Work closely with cross-functional teams, including product managers, engineers, and data scientists, to identify opportunities for integrating AI and LLMs into new and existing products and workflows.

Research and Innovation: Stay current with the latest advancements and trends in AI, LLMs, prompt engineering, and related technologies, and apply this knowledge to drive innovation and maintain our competitive edge.

Performance Analysis: Monitor, analyze, and interpret the performance of AI models and systems, providing actionable insights and recommendations for continuous improvement. Use statistical modelling analysis, Machine Learning, Data mining techniques to extract actionable insights from large and complex datasets.

Conduct exploratory data analysis to uncover hidden relationships and opportunities for optimizations.

Algorithm Development:

Design, develop, deploy advance algorithms to solve complex business problems.

Optimize algorithms for scalability, performance, and accuracy.

Stay abreast of the latest advancements in Machine Learning and Artificial Intelligence and continuously improve modelling techniques.

Collaboration and communication:

Collaborate with Model Risk Management and Data Engineers, business analysts, product managers to define project requirements and deliver solutions.

Communicate findings and recommendations to technical and non-technical stakeholders.

Act as subject matter expert on Data Science methodology and best practices.

Data management and governance:

Work with Data engineers to ensure availability, quality, and integrity of datasets.

Develop and implement Data governance procedures to ensure compliance with regulatory requirements and industry standards.

Domain Skills

Good understanding of Banking domain (Wealth, Cards, Deposit, Loans & Insurance etc.)

Functional Skills

Business risk, controls, compliance, and data management.

Nice to have - Knowledge of Finance Regulations, Understanding of Audit Process

Soft Skills

Should have good communication and inter-personal skills.

Mentoring junior members in the team

Ability to thrive in a dynamic and fast-paced environment.

Contribute to organizational initiatives in wide ranging areas including competency development, training, organizational building activities etc.

Proactive approach in solving problems and eye for details.

A strong team player

Basic Qualifications:

Bachelor’s degree in quantitative field (Computer science, engineering, mathematics, machine learning, statistics)

5-8 years of experience in Data science role mainly leveraging latest AI, LLM and Prompting skills

Proficiency in programming languages like Python, R, or SAS

Experience in Python and relevant libraries (Numpy, Pandas, Scikit learn etc.)

Coursework related to Machine learning, Deep learning (NLP / OCR) and Programming

Good with understanding of LLMs and hands on experience on use and implementation of AI tools and prompt engineering

Hands on application experience using common ML frameworks such as TensorFlow, PyTorch, OpenAI and LangChain

Experience with big data platforms (e.g. Hadoop, Spark) and SQL databases

Demonstrated ability to write high quality code, develop Machine Learning models

Excellent verbal and written communication skills

Problem solving and Story telling skills to provide recommendations and generate actionable Business Insights.

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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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