Senior Decision Scientist- Agentic Analytics Senior Decision Scientist- Agentic Analytics

About the Role

Key Responsibilities

• Propose and execute a comprehensive measurement strategy for Salesforce's external Agents, leveraging product analytics, telemetry, and instrumentation to ensure high-quality event capture in Agentforce logs and Salesforce Data Cloud.
• Integrate Agentforce data with Google Analytics (GA/GA4) for web-analytics-style reporting on agent engagement and funnel impact.
• Partner with engineering to design Data Model Objects and semantic layers in Salesforce Data Cloud, building scalable data foundations for conversational, natural language-driven analytics in Tableau Next.
• Ensure semantic consistency and governance across metrics to reduce fragmented reporting.
• Lead projects that integrate real-time web analytics signals via APIs with Salesforce Data Cloud, enriching customer profiles by linking anonymous web traffic to known identifiers such as Trailblazer ID, Lead ID, or Contact ID from CRM.
• Identify and close data coverage gaps to improve personalization and attribution accuracy.

Requirements

• 7+ years of experience in analytics, decision science, or product data roles.
• Strong expertise in SQL and working knowledge of Python or R.
• Hands-on experience with web analytics tools such as Google Analytics/GA4 and event log/telemetry data.
• Proven track record designing data models and semantic layers in platforms like Salesforce Data Cloud, Snowflake, or BigQuery.
• Ability to translate complex data into business insights related to funnel, lead generation, and pipeline contribution.
• Strong cross-functional collaboration skills across data engineering, product, and business teams.

Nice to Have

• Experience with Tableau or other BI platforms.
• Exposure to conversational analytics.
• Background in customer data platforms (CDPs), identity resolution, or real-time data streaming.
• Familiarity with AI agent frameworks such as Agentforce, chatbots, or conversational AI systems.
• Curiosity to learn and adopt new tools in emerging product spaces.

Qualifications

• Educational background is not explicitly specified, but extensive experience in analytics roles is required.

Benefits & Perks

• Time off and leaves
• Perks such as discounts, commuter benefits, and educational reimbursement
• Mental health, parenting, and childcare resources
• Medical, dental, and vision insurance
• Paid parental leave
• Life and disability insurance
• 401(k) plan
• Employee stock purchasing program