Associate - Data Intelligence Group

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in the Data Intelligence team to partner with the Business.

As an analyst in the Data Intelligence Group (“DIG”), you will be responsible for identifying, developing, and supporting implementation of high-impact, high-priority opportunities to use data for better client/advisor outcomes or for Solutions business opportunities.

This is an exciting opportunity to join a small, dynamic team with the resources and impact of one of world’s largest companies.

Job Responsibilities

• Create technical design, execute and implement of Data Intelligence use cases to drive better outcomes or expand business opportunities, by:
• Design architecture (including front-to-back design, authoritative data sources, how to deliver data to end users, vendor intelligence and build vs. buy recommendation)
• Partner with Technology, Operations, vendors, and other functions to implement use cases, with supervision from DIF
• Handle tactical projects dealing with automation
• Partner with the DIG Data Strategists in building, scoring, and presenting use cases to the Data Intelligence Forum (DIF) for approval
Ensure ongoing successful delivery of team priorities defined by DIG team leads

Required qualifications, capabilities, and skills

• Strong analytical skills and business orientation with proven ability to use data and analytics to drive innovation and business results
• Strong programming skills and demonstrated history of completing projects using Python(pandas, numpy, scipy, scikit learn)
• 5+ years of experience in applied modeling and analytical problem solving with a strong quantitative focus
• Demonstrated experience working with engineering, developers, and other technology teams
• Critical thinking skills and the ability to work through problems, develop creative solutions, and act on those ideas through completion
Bachelor’s degree; advanced degree in a quantitative discipline (math, statistics, economics, engineering, etc.)

Preferred qualifications, capabilities, and skills:

• CFA/FRM charter holder
• SQL experience preferred to handle large unstructured data, exposure to LLMs