The Data Science Manager / Data Delivery Manager leads analytics and data science delivery, capability building, and practice growth at Grant Thornton (GT). This role is accountable for solution quality, delivery excellence, team performance, client outcomes, and strategic growth of GT’s analytics and data science offerings. The Manager partners with leadership, sales, and clients to drive data‑driven value realization at scale.
- Lead data science programs and multiple concurrent client engagements
- Define and execute analytics and data science delivery strategy aligned to GT objectives
- Establish GT standards, accelerators, frameworks, and best practices for analytics and ML delivery
- Drive adoption of enterprise data platforms, analytics, and reporting solutions
- Oversee solution governance, quality assurance, and delivery outcomes
- Manage teams, resourcing, utilization, and delivery metrics
- Mentor and develop leads, consultants, and associates
- Partner with sales, leadership, and solutioning teams for pursuits, proposals, and estimations
- Ensure data governance, security, regulatory compliance, and risk management
- Track client value realization, adoption, and analytics maturity progression
Microsoft Azure
Azure Analytics Platforms: Microsoft Fabric, Azure Synapse, Azure Machine Learning
Power BI (enterprise reporting, governed analytics adoption)
Azure Data Services (SQL, Data Lake, Integration Services)
Multi‑Cloud Awareness
AWS analytics and ML platforms (solution oversight level)
Google Cloud analytics platforms (solution oversight level)
Delivery & Management Tools
Project and delivery management tools (Azure DevOps / GT‑approved tools)
Analytics accelerators, reusable assets, and reference architectures
Governance & Compliance
Data governance, security, and compliance frameworks
Model risk management and responsible AI practices
- Strong people leadership and delivery management capability
- Proven strategic analytics and data science leadership
- Deep understanding of data‑driven value realization and analytics adoption
- Ability to scale analytics programs across teams and clients
- Strong stakeholder influence, executive communication, and decision‑making skills
- Experience balancing innovation, governance, and commercial outcomes
Required certifications
- Microsoft Certified: Azure Data Scientist Associate (DP‑100)
Or
AWS Certified Solutions Architect
Or
Google Professional Data Engineer
