AI-Ready Data Analytics Lead

Veeva; Toronto; On-site; CAD 200,000 - 300,000; Full time

Benefits offered by this job

Medical, dental, vision, and basic lif

PTO and company-paid holidays

Retirement programs

1% charitable giving program

Job summary

Veeva Systems is seeking a Data Analytics Lead to own the data platform, drive AI-ready analytics, and mentor a growing team across data analysts and engineers. You will partner with product, client services, and implementation teams to surface insights that shape product strategy and client deliverables, while scaling the data architecture for enterprise-scale use.

Ideal candidates bring 10+ years in data science/engineering, pharma/life sciences exposure, and a strong background in SQL/Python

Qualifications

• 10+ years of progressive experience in data science/analytics and/or data engineering, including managerial capacity.
• Recent work experience in the pharmaceutical or life sciences industry.
• Undergrad or masters in a technical discipline (computer science, statistics, engineering, math, physics, etc.).

Responsibilities

• Modern Data Architecture & Engineering: Upgrade data architecture to be AI-ready and accessible.
• Customer Data Integrations: Lead data integrations with customer systems with Solutions Engineering.
• Product Analyses: Enhance analytics and measurement insights with the product team.
• Custom Analyses: Deliver client-specific analytical requests with Client Services.
• Leadership & Team Mentorship: Direct and grow a team of data analysts and data engineers.

Skills

SQL & Python

Data modeling

Quantitative analysis

Large data sets

AI-ready architecture

Leadership experience

Pharma/Life sciences exposure

Education

Bachelor's/Master's in CS/Stats/Engineering

Job description

Veeva Systems is seeking a Data Analytics Lead to own the data platform, drive AI-ready analytics, and mentor a growing team across data analysts and engineers. You will partner with product, client services, and implementation teams to surface insights that shape product strategy and client deliverables, while scaling the data architecture for enterprise-scale use.

Ideal candidates bring 10+ years in data science/engineering, pharma/life sciences exposure, and a strong background in SQL/Python