Full Job Description
<h2><strong>Who we are </strong></h2>
<h3><strong>About Stripe</strong></h3>
<p><span style="font-weight: 400;">Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.</span></p>
<h3><strong>About the team</strong></h3>
<p>The Data Science & Analytics organization at Stripe partners with teams across the company to drive rigorous, data-informed decision-making at scale. Within this org, the <strong>Verifications</strong> and <strong>Greater China (GCN)</strong> data teams deliver critical analytical and data science work — from identity verification and risk modeling to market-specific growth insights — that directly shapes Stripe's ability to serve users safely and expand into new markets.</p>
<p>Today, the team comprises ICs distributed across Singapore and India, supporting two high-impact pillars. We are looking for a founding Data Science Manager based in <strong>Bengaluru</strong> to build and lead this growing regional footprint from the ground up.</p>
<h2><strong>What you’ll do</strong></h2>
<p>This is a rare <strong>0 → 1 leadership role</strong> with a dual mandate:</p>
<h3>Pillar 1: Direct Team Leadership</h3>
<ul>
<li>Manage a team of Data Scientists and Data Analysts (currently 4 ICs across India and Singapore) spanning the Verifications and GCN workstreams.</li>
<li>Own roadmap prioritization, execution quality, and stakeholder alignment for both workstreams.</li>
<li>Drive hiring for open and future roles in India, building a high-caliber data team in a competitive talent market.</li>
<li>Foster IC growth through real-time coaching, mentorship, career development, and performance management.</li>
</ul>
<h3>Pillar 2: Regional Data Craft Lead (India Office)</h3>
<ul>
<li>Serve as the founding data craft leader for Stripe's India office. Set quality standards, establishing community rituals (knowledge sharing, peer reviews, office hours), and cultivating a strong local data culture.</li>
<li>Act as the go-to point of contact for data craft standards, tooling, and best practices for co-located analysts, even those outside your direct reporting line.</li>
<li>Partner with managers and leads across the broader Data org to ensure consistency in methodology, tooling, and quality bar.</li>
<li>Support onboarding and integration of new data hires in the Bengaluru office.</li>
<li>Over time, this role has the potential to evolve into a <strong>Center of Excellence (COE)</strong> model — becoming the single point of data leadership in India across multiple product pillars (e.g., Payments, Growth, Marketing), not just Risk.</li>
</ul>
<p> </p>
<h3><strong>Responsibilities</strong></h3>
<ul>
<li>Build, manage, and develop a high-performing, geographically distributed data team </li>
<li>Define and drive the data roadmap in close partnership with product, engineering, and business stakeholders — ensuring analytical work is tightly coupled to business outcomes.</li>
<li>Establish and raise the bar on analytical rigor, experimentation frameworks, and data science best practices across the team.</li>
<li>Recruit and retain exceptional data talent, crafting a compelling hiring narrative anchored in local leadership and craft excellence.</li>
<li>Champion a culture of technical excellence, intellectual curiosity, and operational discipline.</li>
<li>Collaborate with cross-functional partners and other data leaders globally to align priorities, share learnings, and maintain org-wide consistency.</li>
<li>Communicate insights, recommendations, and team progress clearly to senior leadership.</li>
</ul>
<h2><strong>Who you are</strong></h2>
<p><span style="font-weight: 400;">We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.</span></p>
<h3><strong>Minimum requirements</strong></h3>
<ul>
<li><strong>10+ years of experience</strong> in data science, analytics, or a related quantitative field, with 3<strong>+ years in a people management role</strong> leading data scientists or analysts.</li>
<li>Strong technical foundation in SQL, Python/R, statistical modeling, and experimentation design.</li>
<li>Demonstrated ability to translate ambiguous business problems into structured analytical frameworks and actionable insights.</li>
<li>Experience managing and developing IC talent across multiple levels, including coaching, career pathing, and performance management.</li>
<li>Excellent communication and stakeholder management skills — able to influence without authority across functions and time zones.</li>
<li>Proven ability to drive alignment and execution across distributed, cross-functional teams.</li>
</ul>
<h3><strong>Preferred qualifications</strong><span style="font-weight: 400;"> </span></h3>
<ul>
<li>Advanced degree (M.S. or Ph.D.) in a quantitative discipline such as Statistics, Economics, Computer Science, Mathematics, or a related field.</li>
<li>Experience working in the payments, fintech, or financial services industry.</li>
<li>Prior experience building and scaling data teams in a high-growth environment — particularly standing up 0 → 1 functions or teams</li>
<li>Track record of being a builder. Someone who has personally architected the rituals, standards, hiring bar, and craft culture for a data team from the ground up</li>
<li>Familiarity with risk, verifications, or compliance-related data domains.</li>
<li>Experience operating across APAC markets and navigating the nuances of multi-region team management.</li>
<li>Passion for developing others and creating environments where ICs do the best work of their careers.</li>
</ul>