Vice President of Data Science

Job Description:

Fidelity Labs seeks a Vice President of Data Science to join a Labs startup. The startup's focus is building innovative technology for financial services, with an expertise in artificial intelligence to accelerate growth. This role will lead the data science strategy and roadmap, working with a data science team, responsible for the design, implementation, testing and delivery of solutions that are reinventing how financial services firms market and sell their solutions. This role will be a key member of the startup team, serving as the face of data science for internal and external audiences, and will actively collaborate with the product and development teams.

The Team

We are Fidelity Labs, Fidelity Investments' in-house fintech incubator with a mission to build new businesses to drive growth for Fidelity. We seek to shape the future of our industry by building new products and services to improve the lives of the diverse set of customers, businesses and financial institutions we serve.

• Strong, proven, communication, collaboration and leadership skills
  • You have prior leadership experience understanding business objectives and developing solutions
  • You can successfully communicate/convince other senior leaders of your plans and progress, both within an organization and with clients
  • You are able to lead a team to accomplish that plan, in an agile and collaborative environment
  • A passion for excellence and a desire to mentor and develop talent
• Experience in delivery of data science to a product, ideally at a startup, lab or early stage company, in the field of AI-driven personalization, financial services, marketing and/or business development
• Proven experience building analytics, as well as leveraging large language models, to deliver useful insights from large datasets
• Hands on expertise in data extraction, cleaning, and preparation; feature extraction; model training and evaluation; model deployment
• MS/PhD in data science, statistics or similar quantitative field, plus 5 or more years senior level practical data science experience in the financial or similar domain
• Hands On Experience with Data Science, ML, AI, and LLM tools is plus (examples: Sagemaker Python, Scikitlearn, SQL, Bedrock, OpenAI)