Lead and grow the team. Manage and develop data scientists and analytics engineers. Recruit, interview, and onboard top talent as the team scales. Create shared standards for what great data work looks like, and coach the team to get there. Establish rituals that build team cohesion and support technical growth.
Set the technical bar. Hold high standards for experimentation, analysis, insights, metric design, and data modeling. Ensure that Clay remains at the forefront of the latest innovations in AI for data science and analytics.
Relentlessly focus on impact. Ensure the team is making the right tradeoffs. Keep the team focused on work that actually changes decisions and meaningfully impacts the business trajectory of Clay, and leave the rest.
Strategically partner and prioritize across the business. Own staffing across partner areas to ensure every key stakeholder has the support they need, while holding a high bar for impact and pushing back where needed. Ensure partners are making data-informed decisions, and that they have the tooling, insights, and partnership they need to do so.
Shape product and business strategy. Directly inform what we prioritize using data; opportunity size new potential areas for investment and proactively identify potential new directions through analysis and insights. Set the narrative internally using numbers.
Define our key measurement frameworks. Partner with stakeholders to define our business and product goals. Lead the development and championing of key metrics; ensure our most important metrics are properly instrumented and monitored. Create a data-obsessed organization.
Develop a deep understanding of and empathy for our users. Partner with UXR and customer feedback teams to create the most comprehensive understanding of what Clay users, buyers, and prospects want and need.