Strategic Analytics Lead, Commercial Insights

CSL Plasma; Summit (NJ); Hybrid; USD 140,000 - 200,000; Full time

Job summary

CSL Plasma seeks a Senior Manager, Commercial Analytics & Insights to lead analytical projects that support marketing and sales strategies in the US. The role collaborates with Sales, Marketing, Forecasting and Data Strategy teams to deliver data-driven insights and KPI dashboards, shaping the commercial plan.

The candidate will apply advanced analytics techniques (regression, clustering, time-series, neural networks) using SAS, R, Python and BI tools, and will influence leadership with clear,

Qualifications

• Bachelor's degree or above in a quantitative field or equivalent experience.
• Minimum 7+ years in Commercial Analytics, Forecasting, Advanced Analytics, and Market Research.
• Proficiency with analytics tools and data sources, including pharmaceutical data.
• Strong leadership and communication skills; ability to influence stakeholders.

Responsibilities

• Lead analytics projects across performance analytics, ROI, forecasting and market research.
• Develop and apply advanced analytics methodologies for data-driven decisions.
• Hands-on analytics using SAS, R, Python; deliver actionable insights via BI dashboards.
• Collaborate with Sales, Marketing, Forecasting, IT to evolve CRM and data warehouse.
• Identify KPIs and communicate findings to executives and cross-functional teams.
• Lead Sales Force Effectiveness studies and support targeting and promotions.

Skills

Advanced analytics

SAS

R

Python

Power BI

Alteryx

CRM systems

Data strategy

Education

Bachelor's degree or above

Master's degree or MBA

Tools

SAS

R

Python

Power BI

Alteryx

Excel

Job description

CSL Plasma seeks a Senior Manager, Commercial Analytics & Insights to lead analytical projects that support marketing and sales strategies in the US. The role collaborates with Sales, Marketing, Forecasting and Data Strategy teams to deliver data-driven insights and KPI dashboards, shaping the commercial plan.

The candidate will apply advanced analytics techniques (regression, clustering, time-series, neural networks) using SAS, R, Python and BI tools, and will influence leadership with clear,