Fidelity
VP,DataSciencePracticeLead
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“VP, Data Science Practice Lead at Fidelity. Skills: Data Science, Leadership, AI, Machine Learning. Identify and scope high-impact use cases. Drive experimentation and pilot solutions”
What You'll Achieve.
Make measurable operational improvements; Align solution delivery with business objectives; Validate solution approaches; Quantify business value; Quickly learn what works; Adjusting based on data-driven learnings; Objectively evaluate impact; Ensure multiple workstreams progress on schedule; Deliver high-quality results; Ensure solutions are scalable, well-documented, and maintainable; Create efficiencies and drive value; Ensure solutions fit seamlessly into business operations; Communicate end-to-end impact of AI solutions; Communicate total cost (build/maintain); Communicate risks and controls; Communicate value realized against agreed KPIs; Drive adoption and change management so solutions are used and sustained
Industry & Context.
Problem-solving orientation; Ask the right questions; Pursue whatever data or analyses are needed to answer them
What They're Looking For.
Must Have
Bachelor's degree in Statistics, Computer Science, Data Analytics, or a related quantitative field, 15 years of hands-on experience in data science or analytics, at least a few years in a senior or team lead capacity, Proven track record of end-to-end project ownership, Demonstrated ability to work closely with business stakeholders, project management skills, Excellent written and verbal communication skills, problem-solving orientation, data-driven and experimental mindset, Highly detail-oriented, commitment to data quality, validation, and rigorous methodology
Nice to Have
Master’s or PhD in a relevant field, Experience applying data science in internal/corporate operations contexts, Familiarity with operational metrics and challenges, Hands-on experience designing and analyzing experiments, Knowledge of Agile project management or iterative development methodologies, modern NLP and Generative AI techniques, LLM evaluation and observability/tracing practices, Experience implementing safety and compliance guardrails and governance controls for enterprise GenAI deployments, Familiarity with data visualization and BI tools
What You'll Do.
Identify and scope high-impact use cases
Drive experimentation and pilot solutions
Lead prototyping efforts
Quantify business value
test-and-learn approach
Design A/B tests or proof-of-concepts
Define success metrics and KPIs
Guide and mentor data scientists
Provide technical direction and oversight
Manage project portfolios
Ensure workstreams progress
Foster culture of curiosity
Partner with engineering and architecture teams
Implement data science solutions
Oversee development of data pipelines
Integrate models into existing systems
Ensure solutions are scalable
Ensure solutions are well-documented
Ensure solutions are maintainable
Pilot and roll out tools
Translate technical concepts
Present solution performance and insights
How You'll Work.
Team & Collaboration
Work closely with business stakeholders; Partner closely with engineering and architecture teams; Work with business stakeholders (e.g. operations, finance, HR, compliance); Serve as a trusted advisor to cross-functional leaders
Communication Scope
Communicate clearly to both technical and non-technical audiences; Communicate progress, tradeoffs, and recommendations in clear, impactful ways; Translate technical concepts into business terms; Present solution performance and insights to non-technical leaders using compelling storytelling and visualizations; Regularly update stakeholders; Align on success metrics; Excellent written and verbal communication skills; Distill complex analytical findings into clear presentations for non-technical audiences; Communicate data stories and recommendations to influence senior executives and frontline operational teams
Process & Methodology
Project management skills, Prioritize projects by business need and value impact, Manage project portfolios, Ensure multiple workstreams progress on schedule, Deliver high-quality results, Agile project management, Iterative development methodologies
Full Job Description
## ## Job Description: **Data Science Practice Lead** We are seeking an experienced Data Science Practice Lead to help drive and scale data science use cases and AI-enabled capabilities for internal technology and operations. In this Boston-based leadership role, you will focus on internal-facing use cases, supporting teams like customer support/call centers, document workflow, compliance, finance, and other corporate functions. The ideal candidate combines deep technical data science expertise with strong leadership and business collaboration skills. You will guide a team of data scientists to deliver innovative solutions, working closely with business stakeholders and engineering partners to ensure projects are well-scoped, aligned to business needs and enterprise standards. A key aspect of this role is driving experimentation and pilot projects to prove value before scaling solutions to full production. If you are passionate about making measurable operational improvements and can communicate clearly to both technical and non-technical audiences, we want to hear from you. **Key Responsibilities:** * **Identify and Scope High-Impact Use Cases:** Work directly with internal business stakeholders to identify high-value internal problems and frame them into AI use cases. Translate business needs into AI/ML capabilities, experiments, and measurable outcomes that align solution delivery with business objectives. * **Drive Experimentation and Pilot Solutions:** Lead prototyping efforts and experimental pilot programs to validate solution approaches and quantify business value before full-scale deployment. Employ an iterative, test-and-learn approach – designing A/B tests or proof-of-concepts to quickly learn what works and adjusting based on data-driven learnings and business stakeholder input. Ensure success metrics and KPIs are defined for each initiative to objectively evaluate impact. * **Leadership and Team Development:** Guide and mentor a team of data scientists,
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