Lead Data Scientist, Growth Marketing

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. About Slack Slack is the work operating system that brings your people, apps, processes and data together with trusted generative and agentic AI, fueling productivity for every employee in every role. Millions of people work in Slack every day with global teams, partners and customers, sending over 700 million messages and automating processes with over 3 million workflows daily. As part of Salesforce, Slack is where Agentforce, an always-on digital workforce, works alongside your teams and amplifies the impact of sales, service, HR, IT and more. To learn more and get started with Slack, visit slack.com. Role Summary: We are seeking a visionary Lead Data Scientist, Growth Marketing to define the analytical strategy and drive the quantitative engine for Slack’s global web presence. In this senior-most individual contributor (IC) role, you will bridge deep technical data science with high-level business strategy. You will move beyond optimizing local web conversion metrics to connect web behavioral insights directly to overarching business impact—such as customer acquisition, enterprise pipeline generation, and lifetime value. As a technical authority and strategic thought partner to Marketing, Product, and Engineering leadership, you will lead our global web experimentation framework, architect advanced behavioral models, and elevate the analytical capabilities of the broader organization. You will serve as a lead IC who actively mentors, coaches, and guides data analysts and data scientists, with the potential or opportunity to functionally lead and manage quantitative teams. Key Responsibilities: Strategic Business Impact & Growth Vision • Macro Connection: Connect top- and mid-funnel web behavior directly to core business outcomes, enterprise ARR, pipeline velocity, and customer lifetime value (LTV). • Strategic Roadmap: Partner with executive leadership (VPs, SVPs) across Marketing, Product, and Growth Engineering to align web analytics and experimentation strategies with multi-year company growth targets. • Opportunity Prioritization: Identify macro trends, unaddressed user segments, and high-leverage growth opportunities through deep quantitative research and exploratory data analysis. Advanced Experimentation & Causal Inference Leadership • Global Framework Ownership: Lead and evolve Slack’s web experimentation strategy, setting institutional standards for statistical rigor, hypothesis formulation, power analysis, and sample size estimation. • Methodological Depth: Deploy advanced statistical techniques, such as variance reduction (CUPED), sequential testing, synthetic controls, and quasi-experimental designs to measure true incremental lift in complex digital environments. • Experimentation Culture: Drive best practices across product and growth teams to eliminate bias, manage interference/network effects, and scale experiment volume without compromising data integrity. Technical Architecture & Behavioral Data Science • Analytics & Privacy Stack: Serve as the principal architect for the digital measurement ecosystem (e.g., GA4, Adobe Analytics, server-side tracking, GTM) in a privacy-first, first-party data landscape. • Predictive & Behavioral Modeling: Build and operationalize session-stitching, multi-touch pathing analysis, propensity modeling, and advanced behavioral clustering (e.g., K-Means) to profile visitors into targetable segments. • Scalable Data Ecosystem: Collaborate with Data Engineering to design robust web data pipelines and automated reporting layers that support self-service insights for growth teams. Team Leadership, Mentorship & Functional Management • Technical Mentorship: Act as a force multiplier by coaching, mentoring, and guiding data analysts and junior/mid-level data scientists on statistical methodology, SQL/Python code quality, and strategic thinking. • Team & Pod Leadership: Demonstrate the aptitude and leadership (formal or informal) to lead project pods, manage sprint priorities, or transition into team management as the analytics organization expands. • Rigor & Governance: Establish peer review standards for analytical models, code repositories, and exper