About the Data Science Team
The team consists of 40+ Data Scientists covering key analytics for the company, including product, people, marketing and operational analytics. Their insights drive company and team-level goal setting, identify strategic and tactical opportunities, guide product roadmaps, and measure the impact of product delivery on business metrics. They play a crucial role in bringing AI-powered product strategies to market. Led by senior pillar leads, this distributed team ensures execution rigor through goal measurement and partners closely with the CEO, C-suite, and Finance to align product analytics with overall business performance.
About the Role
The Vice President of Data Science will be responsible for cross-functionally partnering across all areas of the business to scale and further mature the product decisions of our growing company. You will lead the Data Science function, providing strategic direction for product, marketing, people and operational analytics, as well as all business functions. This senior leadership role is pivotal in driving data-driven decision-making across the organization, ensuring the company leverages data to drive investments for our product initiatives, optimize performance, innovate, and achieve business goals. The VP requires strong leadership skills, exceptional statistical domain expertise, and the demonstrated ability to motivate and inspire a growing team. This role reports to the Chief Product Officer.
Responsibilities
- Lead, develop and grow a team of 40+ Data Scientists within product, people, operations and marketing, who elevate the entire product development process through research, goal-setting and better decision-making.
- Define opportunities, size various initiatives and evaluate the impact of the opportunities.
- Co-own the company’s product development roadmap together with senior leaders in product management, engineering and design/user research.
- Guide the leadership team on setting company-wide goals that inform and support our long-term product strategy.
- Drive critical company-wide initiatives including Data Science infrastructure, product quality, commission plan, sales and marketing effectiveness and people team initiatives.
- Manage team execution at scale with ambitious but achievable goal-setting, inspiring sense of urgency, expecting high standards, leveraging direct reports and team managers.
- Build agility into the organization to go after opportunities / shift priorities as needed.
- Uphold key leadership values: lead with why, make it count, own it, choose teamwork, and say what you mean.
Must-Have Qualifications
If you don't think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we're looking for someone excited to join the team.
- 12+ years of analytics experience with 8+ years of management experience.
- Strong expertise in product, marketing, and operational analytics.
- A well-balanced combination of big-picture thinking, ability to thrive in ambiguity, exceptional problem solving skills and patience to teach others and uphold a high bar.
- Strong analytical and technical skills. You should be able to guide your team to delivering high-quality analyses in a scalable way.
- Experience working in experiment-driven product development in close partnership with product managers, engineers and designers.
- Strong communication skills and ability to build strong relationships cross-functionally and with senior leadership.
- Bachelor’s, Master’s, Doctoral degree in one of the following areas; Statistics, Engineering, Analytics, Math, Computer Science, Operations Research.
Nice-to-Have Qualifications
- Experience working in a marketplace company.
- Public company experience.
- Experience managing a remote / distributed team.
Thumbtack is a virtual-first company, meaning you can live and work from any one of our approved locations across the United States, Canada or the Philippines.
The expected salary range for the role is currently $360,000 - $400,000. Actual offered salaries will vary and will be based on various factors, such as calibrated job level, qualifications, skills, competencies, and proficiency for the role.
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