Sr. Data Scientist - Vice President

Job Summary

The Sr. Data Scientist is responsible for establishing and implementing new or revised data science and machine learning application systems in coordination with the Technology team. The overall objective of this role is to lead the applications systems analysis, advanced model development, and programming activities for our data science initiatives.

• Strategic Partnership:
  Partner with multiple management teams to ensure appropriate integration of data science functions to meet goals. Identify and define necessary system enhancements to deploy new data products and process improvements, with a focus on leveraging machine learning.
• Problem Resolution:
  Resolve a variety of high-impact problems and projects through in-depth evaluation of complex business processes, system processes, and industry standards, applying advanced statistical analysis and machine learning modeling techniques.
• Technical Leadership & Expertise:
  • Developing complex machine learning models using the Python AI/ML stack.
  • Designing and implementing solutions for anomaly detection, noun entity recognition (NER), and rule-based compliance policies.
  • Building and deploying Agentic AI solutions using Large Language Models (LLMs).
• ML Lifecycle Management:
  Utilize advanced knowledge of the machine learning model lifecycle to develop and enforce standards for coding, testing, debugging, and implementation of scalable, production-grade models.
• Business Integration:
  Develop a comprehensive knowledge of how areas of business, such as architecture and infrastructure, integrate to accomplish business goals and to ensure the effective deployment of data science capabilities.
• Innovation & Solutioning:
  Provide in-depth analysis with interpretive thinking to define complex business issues and develop innovative, data-driven solutions and machine learning models.
• Mentorship:
  Serve as an advisor or coach to mid-level data scientists and analysts, allocating work as necessary and fostering a culture of technical excellence.
• Risk Management:
  
  Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm’s reputation and safeguarding Citigroup, its clients, and assets. This includes driving compliance with applicable laws, rules, and regulations related to data and AI, adhering to Policy, applying sound ethical judgment, and escalating, managing, and reporting control issues with transparency.

• Experience:
  
  6-10 years of relevant experience in a Data Science, Machine Learning, or a related Applications Development role with a strong focus on quantitative analysis.
• Technical Proficiency:
  Extensive experience in statistical analysis, machine learning model development, and programming of software applications, specifically with the Python AI/ML stack (e.g., Scikit-learn, Pandas, Num Py, Tensor Flow, PyTorch).
• Project Implementation:
  Proven experience in managing and implementing successful data science projects from conception to production.
• Subject Matter Expertise:
  Recognized Subject Matter Expert (SME) in applied machine learning, with deep knowledge in one or more of the following:
  • Anomaly Detection
  • Natural Language Processing (NLP), particularly Noun Entity Recognition (NER)
  • Agentic AI using Large Language Models (LLMs)
  • Rule-based systems for compliance and policy implementation
• Preferred
  
  Skills:
  
  Familiarity with the SAS programming language and/or Java-based microservices architecture is a plus.
• Adaptability:
  Ability to adjust priorities quickly as circumstances dictate in a fast-paced environment.
• Leadership:
  Demonstrated leadership and project management skills.
• Communication:
  Consistently demonstrates clear and concise written and verbal communication, with the ability to convey complex technical concepts to diverse audiences.

• Required:
  
  Bachelor’s degree/University degree in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering, or equivalent experience.
• Preferred:
  Master’s degree or Ph.D. in a relevant quantitative discipline is highly preferred.

Technology

Applications Development

Full time