Salesforce

Technology

SeniorAnalyst,RecruitingDataAnalytics

$99–150k United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Analyst, Recruiting Data Analytics at Salesforce. Skills: Predictive modeling, Machine learning, Data analytics. Build predictive analytics models. Validate predictive analytics models”

Industry & Context.

Technology
Problems you'll solve

Predictive insights; Data-driven solutions

What They're Looking For.

Must Have

4+ years of professional experience in data analytics, people analytics, or recruiting analytics, Proven track record of delivering predictive insights, Foundational knowledge of machine learning concepts and predictive modeling methodologies, Proficient in Python or R for data manipulation, statistical analysis, and machine learning libraries, Intermediate SQL skills for querying, data preparation, and pipeline optimization, Proven experience designing and maintaining complex Tableau dashboards

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

Build predictive analytics models

Validate predictive analytics models

Deploy predictive analytics models

Forecast hiring trends

Forecast attrition risks

Forecast talent supply gaps

Apply machine learning techniques

Uncover deeper insights within recruiting and workforce planning

Translate complex ML model outputs into actionable

Create clear data stories for recruiting leadership

Maintain key Tableau dashboards

Manage key Tableau dashboards

Integrate predictive insights into user-friendly visualization tools

Integrate advanced data models into user-friendly visualization tools

Automate manual reporting workflows

Automate pipeline tasks

Scale insight delivery across the organization

Partner with Workforce Planning

Partner with Data Engineering

Scale infrastructure for advanced analytics

Adapt quickly to changing priorities

Ensure timely delivery in a dynamic environment

How You'll Work.

Team & Collaboration

Cross-functional collaboration; Data Engineering teams; Finance teams; Workforce Planning teams; IT teams

Communication Scope

Data storytelling

Full Job Description

_To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts._ Job Category Data Job Details ****About Salesforce**** Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. The Recruiting Analytics Insights & Research (RAIR) team is seeking a detail-oriented, mid-career Analyst. As part of the Recruiting Organization and the larger people analytics umbrella at Salesforce, we act as strategic consultants for the Recruiting Organization, providing informed analysis and business acumen that challenge myths and status quo mindsets. We leverage Salesforce’s cutting-edge technology stack, embracing the evolution of insight delivery beyond traditional BI and analytics consulting at scale. The RAIR team engages with stakeholders during critical moments, understanding their business needs and offering strategic, data-informed solutions with actionable recommendations. This role will support and evolve some of our most critical and highly visible self-service dashboards as we develop agentic and conversational analytics products for Salesforce’s next generation of Workforce Planning and Recruiting Platforms. **Responsibilities** * \- Predictive Modeling: Build, validate, and deploy predictive analytics models to forecast hiring trends, attrition risks, and talent supply gaps. * \- ML Integration: Apply machine learning techniques (such as regr

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