Vice President, Data Science

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

The Purpose of Your Role

Fidelity Workplace Investing is seeking an experienced Data Science leader to lead a team focused on powering intelligent, personalized digital experiences for our customers. This role will partner closely with product, engineering, design, and business leaders to identify high-value opportunities and deliver AI-powered solutions that drive meaningful customer and business outcomes.

As team leader, you will be responsible for advancing our AI strategy in this area, developing and implementing best practices, delivering machine learning and generative AI capabilities, and enabling the responsible adoption of emerging AI technologies. You will lead a highly skilled team of data scientists through the full AI lifecycle-from experimentation and model development to deployment, monitoring, governance, and continuous optimization.

The ideal candidate combines deep technical expertise with strong business acumen and has experience delivering AI solutions at scale. This includes personalization, predictive modeling, recommendation systems, large language models (LLMs), agentic AI systems, and responsible AI practices. You will consult with business leaders to help ideate and shape the next generation of Fidelity's personalized experiences.

The Skills You Bring

• People management: Proven ability to mentor and coach data scientists on project delivery and long-term skill development.

• Stakeholder and relationship management: Strong ability to translate business opportunities into AI-driven solutions that deliver measurable outcomes.
• Cross-functional Collaboration: Partner with executive leadership, product, and engineering teams to integrate AI models into customer-facing products

• Written and verbal communication skills: Ability to communicate complex AI concepts, risks, and opportunities to both technical and non-technical audiences.
• AI Development: Expertise across the AI/ML lifecycle, including experimentation, feature engineering, model development, deployment, measurement, monitoring, and governance.
• Modeling: Deep understanding of statistics, predictive modeling, recommendation systems, experimentation, causal inference, and optimization techniques.
• GenAI: Experience evaluating, deploying, and governing generative AI solutions, including large language models, retrieval-augmented generation (RAG), AI agents, and multimodal AI systems.
• Tools: Strong proficiency in Python, SQL, MLOps, and modern AI/ML development frameworks (e.g. AWS Sagemaker).

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• Master's or PhD in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline.

• 12 years of experience in artificial intelligence, machine learning, advanced analytics, data science, or related fields.
• Significant experience leading teams, programs, and organizational AI initiatives.