Senior Analytics Consulting Manager

Responsibilities

• Manage the end-to-end delivery of analytics projects, from scoping and planning to execution and delivery.
• Translate ambiguous business questions into tractable data analysis projects.
• Interpret and investigate data and statistical questions that arise through the delivery of client work.
• Collaborate with cross-functional teams, including Data Science, Engineering, and Product Management, to ensure alignment on project goals and deliverables.
• Serve as the primary point of contact for clients, addressing any concerns or issues that may arise during the project lifecycle.
• Monitor project progress and performance, proactively identifying risks and implementing mitigation strategies as needed.
• Stay abreast of industry trends and best practices in healthcare analytics, incorporating new insights and technologies into our service offerings.

Requirements

• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.
• Minimum of 8 years of experience in healthcare analytics or related field, with a proven track record of delivering analytics solutions to clients.
• Strong project management skills, with experience leading cross-functional teams and managing client relationships.
• Excellent communication and presentation skills, with the ability to convey complex analytical concepts to non-technical audiences.
• Proficiency in data analysis tools and programming languages such as SQL, Python, or R.

Nice-to-Haves

• Experience working in a consulting or professional services environment, preferably within the healthcare industry.
• Experience with cloud-based analytics platforms such as AWS, Google Cloud Platform, or Azure.
• Familiarity with healthcare data standards and regulations, such as HIPAA and GDPR.
• Advanced analytical skills, including predictive modeling, machine learning, and data visualization.

Expectations of AI Use

• Applies AI strategically, knowing how to use the right tools at the right time to solve problems or generate new ideas.
• Uses AI to accelerate feedback loops, test ideas, and make informed decisions faster.
• Demonstrates curiosity and initiative in exploring new AI tools and workflows relevant to their role.
• Brings a reflexive AI mindset and uses AI as a natural part of their process to iterate, research, and deliver better work.
• Comfortable working in AI-enhanced environments across writing, data analysis, content creation, or design.
• Regularly leverages AI tools such as Notion AI, Perplexity, Claude, Descript, Runway, Midjourney, or Microsoft Copilot.