AI-Driven Pharma Analytics Engagement Lead

MathCo; Boston (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

MathCo is seeking a highly experienced Engagement Lead - Pharma and Life Sciences Analytics to partner with leading life sciences clients in solving complex business challenges through data-driven insights and strategic consulting.

You will lead senior stakeholder engagements, translate business challenges into analytical frameworks, guide cross-functional teams including data science and engineering, and deliver executive-level recommendations.

Qualifications

• 10–14 years of experience in pharmaceutical consulting or commercial analytics.
• Proven leadership of client-facing engagements with executive stakeholders.
• Proficient in SQL, Python; experience with Power BI/Tableau; cloud analytics familiarity.

Responsibilities

• Lead pharma and life sciences analytics engagements with senior stakeholders.
• Translate business challenges into analytics frameworks and insights.
• Mentor junior consultants and collaborate with data science/engineering teams.
• Present findings and strategic recommendations to executives and cross-functional teams.

Skills

Brand Analytics

Commercial Analytics

Market Performance Analytics

Customer Segmentation

Omnichannel Analytics

Promotional Effectiveness

Launch Analytics

Lifecycle Analytics

SQL

Python

Power BI

Tableau

Cloud AI

Generative AI

Stakeholder Management

Executive Storytelling

Education

Bachelor's degree (Life Sciences / related)

Master's degree preferred

MBA or PhD preferred

10–14 years pharma consulting/analytics

Tools

SQL

Python

Power BI

Tableau

Cloud platforms (AWS/GCP)

Job description

MathCo is seeking a highly experienced Engagement Lead - Pharma and Life Sciences Analytics to partner with leading life sciences clients in solving complex business challenges through data-driven insights and strategic consulting.

You will lead senior stakeholder engagements, translate business challenges into analytical frameworks, guide cross-functional teams including data science and engineering, and deliver executive-level recommendations.