Location: Based in our Mountain View or San Francisco office. Hybrid 2-3x a week In this role you'll lead the full-stack Data Science function for all our Sales stakeholders as we grow Moveworks business from $100M to $1B ARR over the next few years. You will collaborate directly with Sales Operations, Sales Leadership, and Business Strategy teams to continuously enhance our role-specific sales dashboards and execute deep analyses to inform day-to-day sales execution tactics as well as longer term sales strategy. You will partner with your fellow Data Scientists on the Marketing and Customer Success side to continue to jointly develop our best-in-class GTM data infrastructure. You're someone who enjoys the constant combination of deep technical data science work with direct first-hand exposure to business context. You're motivated by proactively finding data insights that make an immediate tangible impact on our Sales results. This role is part of our centralized GTM Operations team and reports to Sr. Director of GTM Operations. What Will You Do? * Build and maintain dashboards for all Sales audiences (AEs, Sales Leaders, SDRs, SDR Managers, Presales, etc.) * Analyze sales performance to identify levers that move the needle in increasing our pipeline generation, conversions, win rates, and overall revenue targets. * Work with Sales Leadership and Sales Operations to develop and implement new sales metrics as our business continues to evolve. * Proactively identify opportunities to improve stakeholder dashboards and data quality. * Build and improve ETL pipelines to deliver new metrics and visualizations. * Contribute to analytics working sessions to empower stakeholders to own their analysis. What You Bring To The Table * 4+ years of experience in analytics. * Experienced in BI tools such as Tableau or Mode Analytics. * Strong collaboration skills, business intuition, attention to detail, and natural curiosity. * Experienced in SQL and Python. * Experienced in data modeling principles and ETL. * Experience in building and maintaining data pipelines. * Experienced in causal inference and predictive analytics.