Manager Commercial Analytics

Surescripts

2d•$153,300 - $187,300•Hybrid

About The Position

The Manager Commercial Analytics will establish a commercial analytics function that provides predictive, actionable insights to Sales, Account Management, Marketing, and Strategy leaders. The role replaces manual, Excel-based modeling built on standard Salesforce reporting with a governed commercial data model in a business intelligence platform, using marketing, CRM, financial, and transactional data to understand the end-to-end customer journey. It is an opportunity to build a new function in an established organization focused on rapid growth. The manager owns the commercial data model, governed metric definitions, queries, dashboard architecture, reporting processes, and analytics intake. They lead and develop a Commercial Analyst, partner across business and data teams, and produce analysis to inform business performance, forecasting, planning, quota allocation, and territory design. The role reports analysis and recommendations to commercial and finance leadership. Surescripts offers a flexible hybrid work model for most positions: employees may work virtually and use offices as collaboration centers, with leadership alignment and agreement. The position is based in the United States and requires valid U.S. work authorization without restrictions; visa sponsorship and employer endorsement for specified academic training programs are unavailable. The role may involve meetings in and out of the office, travel, and using computers and other office equipment. The listed annual base pay range is $153,300–$187,300, with actual pay dependent on factors including qualifications, skills, experience, and location.

Requirements

Bachelor’s degree in a quantitative, business, or technical discipline, or equivalent experience.
At least 8 years of experience in commercial analytics, sales operations, revenue operations, or a comparable analytics function supporting a commercial organization.
At least 3 years directing analysts’ work as a manager or team lead.
Advanced SQL and SAQL skills, including writing, optimizing, and troubleshooting complex queries against Salesforce and CRM Analytics datasets.
Data pipeline fluency sufficient to define upstream data requirements and evaluate delivered data.
Hands-on experience building production data models and dashboards in an enterprise BI platform such as Tableau, Power BI, Sigma, Looker, or a comparable platform.
Deep familiarity with the Salesforce data model, including the limits of what CRM data can support.
Experience embedded in a commercial organization, with direct knowledge of the leading indicators commercial leaders use to manage and forecast the business.
Experience establishing analytics where little or none existed, including building the data model, definitions, and operating cadence.
Executive communication skills, including presenting to and responding to challenges from senior commercial and finance leaders and translating analysis into clear recommendations.
Valid U.S. work authorization allowing employment without restrictions; the employer does not provide immigration sponsorship or employer endorsement for specified academic training programs.

Nice To Haves

Statistical and predictive modeling capability using Python, R, or comparable tools to forecast performance, score accounts likely to buy or expand, and test drivers of results.
Experience with healthcare, Health IT, life sciences, or pharmaceutical data, and familiarity with long, relationship-led enterprise sales cycles.
Experience joining CRM data with product and ERP or financial systems, such as NetSuite, for holistic customer health reporting.
Experience with modern data platforms and transformation tooling such as Salesforce Data Cloud, Databricks, or Snowflake.

Responsibilities

Design, build, and own the commercial data model in the Sales BI platform, bringing end-to-end customer data into a governed source for growth-focused analytics.
Establish and publish governed metric definitions, including bookings, ACV, pipeline coverage, attainment, stage conversion, and cycle time.
Write, optimize, and troubleshoot SQL and SAQL for datasets, dashboards, and models; manage query performance, refresh cadence, and automated data-quality monitoring.
Partner with Business Applications, Marketing, Finance, and Data & Analytics on data model needs, integrations, access control, and data governance; act as the commercial-side product owner for growth team metrics.
Own dashboard architecture, release processes, documentation, and version control; enable leader self-service, including natural-language querying, and retire redundant reports and trackers as coverage expands.
Direct and develop the Commercial Analyst, prioritize the analytics intake queue by business impact, and serve as the escalation point for data and metric-definition disputes.
Produce leading KPI indicators for commercial leaders, such as pipeline creation rate and coverage, stage aging, and progression, and measure performance against benchmarks.
Build forecast and pipeline analytics, including forecast-versus-actual variance by segment and leader, and support forecast calls with evidence.
Build customer journey analytics from first touch through implementation, adoption, and growth.
Identify and support remediation of data conditions that distort records, and measure resulting improvements.
Proactively surface changes, explain their implications, and recommend actions.
Automate recurring reporting cycles using the data model, replacing manual exports, mapping, and deck creation.
Use approved AI tooling for report assembly and first-draft narratives, with human review before publication.
Present analysis and recommendations to commercial and finance leadership and defend the methods, data, and conclusions.
Build and own the analytic foundation for annual target setting, including historical performance, productivity benchmarks, market potential, and growth assumptions.
Model quota allocation and alternatives for the compensation committee in partnership with the compensation team.
Support territory and coverage design, including segmentation, book balancing, and whitespace analysis.