Strategic Finance - Product, AI/ML and Analytics

Senior Data Scientist

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the Team The Finance Data Science team owns the forecasting systems that power Snowflake’s revenue planning and long-term financial strategy. Our work supports corporate planning, executive decision-making, and investor reporting, and we partner closely with Product and Sales to understand customer behavior and product impact. We operate at the intersection of machine learning, statistical research, and corporate finance, building production-grade forecasting infrastructure that is foundational to how the company plans and operates. The Role As a Senior Data Scientist, you will independently lead high-impact modeling initiatives and build production-ready forecasting systems for core financial metrics. You will work on complex, open-ended problems at the intersection of machine learning and business strategy, translating real-world financial questions into rigorous, scalable models. What You’ll Do * Design and implement advanced time-series and probabilistic models (e.g., hierarchical models, state-space models, Bayesian approaches, multivariate forecasting). * Contribute to internal tooling and shared infrastructure that enables scalable forecasting and analytics. * Establish best practices for model evaluation, backtesting, uncertainty quantification, and scenario simulation. * Apply advanced statistical and ML techniques to model customer behavior, product adoption, revenue dynamics, and cost trends. * Drive improvements in automation, monitoring, drift detection, and lifecycle management of forecasting models. * Partner with Finance, Product, and Sales teams to quantify the impact of new initiatives and understand key business drivers. * Mentor and provide technical guidance to other data scientists; raise the bar for modeling rigor and production quality across the team. * What We’re Looking For * Advanced degree in a quantitative discipline (Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science) or equivalent practical experience. * 8+ years of experience building and deploying production-grade ML or statistical systems, with significant experience in time-series modeling. * Deep expertise in probabilistic modeling, forecasting methodologies, and model evaluation techniques. * Strong proficiency in Python and the scientific Python ecosystem; fluency in SQL. * Experience designing systems for large-scale data processing (e.g., Snowflake, BigQuery, Redshift, Spark). * Demonstrated ability to lead technically ambiguous projects with significant business impact. * Excellent communication skills, with experience presenting complex quantitative findings to executive stakeholders. * A track record of elevating technical standards and mentoring other scientists. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Startup Business Development Lead - Snowflake for Startups

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. ROLE OVERVIEW The Startup Business Development Lead will be a pivotal member of a small, agile, and global team. This role acts as a coordination overlay across Sales, Marketing, Product, AI Partnerships, Ventures, and Solutions Engineering teams, with the primary goal of targeting and winning workloads from top AI-native startups. The successful candidate will be a strategic thinker with a passion for the AI/ML ecosystem, dedicated to identifying and nurturing high-potential startups and ensuring their growth with Snowflake. This is a business role that requires intimate understanding of evolving AI technologies. Keys to success include proactive founder engagement, disciplined prioritization, cross-functional execution, and a commitment to measurable business outcomes. KEY RESPONSIBILITIES 1. Build relationships with high-priority AI-native startups * Leverage existing networks and cultivate new relationships to secure introductions to founders of high-potential AI-native startups. * Engage founders through direct outreach, partner referrals, industry events, conferences, and targeted networking opportunities. * Create meaningful founder engagement by connecting startup needs with relevant Snowflake product, go-to-market, and customer opportunities. * Leverage technical knowledge of AI to win trust and build collaboration hypotheses. 2. Prioritize the startup landscape and maintain market intelligence * Develop and maintain a categorized list of high-priority startups, including Tier 1 and Tier 2 companies, based on strategic importance, growth potential, funding, technology trends and alignment with Snowflake. * Continuously monitor venture funding activity, startup formation, product trends, and AI/ML ecosystem shifts to refine prioritization. * Partner with Sales, Marketing, Product, AI Partnerships, Venture, and Solutions Engineering to maintain a unified approach to startup outreach and engagement. 3. Drive growth, adoption, and partnerships on Snowflake * Allocate time strategically, with approximately 80% of efforts focused on Tier 1 startups and 20% focused on other high-potential opportunities. * Facilitate introductions between Tier 1 startup founders and Snowflake Executive Leadership Team members, meaning senior Snowflake leaders who can help deepen strategic relationships. * Provide go-to-market support by helping startups understand how Snowflake enterprise customers may evaluate, adopt, and expand startup solutions. * Support Product-Led Growth, meaning self-serve product adoption and expansion, by promoting Cortex AI products to startups not currently built on Snowflake and creating a path for them to move additional data and workloads onto Snowflake. * Collaborate with Sales and Solutions Engineering teams to help them sell Cortex AI products effectively and understand the consumption patterns, buying motions, and adoption needs of startups. 4. Build demand generation and ecosystem visibility * Identify and recommend high-leverage events, sponsorships, and ecosystem programs that enhance Snowflake visibility and generate quality startup leads. * Contribute to workshops, founder programming, PR initiatives, and other content that helps AI startups understand Snowflake offerings and adoption paths. * Design or support scaled events that create meaningful engagement among startups, venture firms, Snowflake customers, and internal Snowflake stakeholders. 5. Measure outcomes and report progress * Use measurement insights to refine startup prioritization, engagement strategy, and cross-functional operating cadence. * Track, and report progress against objectives including priority startup acquisitions, Snowflake commitment contracts, startup influenced consumption via connected apps on Snowflake etc. * Provide regular reports to management on startup engagement progress, outcomes, successes, challenges, and areas for improvement. * Work with Finance and Sales Operations to ensure accurate tracking of startup adoption, usage, commitments, and engagement metrics. QUALIFICATIONS * 8+ years of experience in business development, partnerships, startup ecosystem development, venture capital, corporate venture, GTM, cloud technology, AI/ML, or a related field. * Proven experience supporting high-growth startups at different stages of growth, with preference for candidates who have startup operating experience or have worked closely with founders. * Strong understanding of the AI technology stack, AI startup ecosystem, venture funding trends, cloud and data platform adoption patterns, and key product trends shaping AI-native companies. * Established network across startup founders, venture capital firms, accelerator ecosystems, enterprise technology leaders, and partner organizations. * Ability to translate Snowflake capabilities into startup-relevant value propositions, including product adoption, customer access, GTM support, and workload growth. * Strong executive presence, communication, presentation, and interpersonal skills, with the ability to engage founders, venture partners, senior executives, sales teams, and technical stakeholders. * Founder empathy and strong judgment in balancing startup needs with Snowflake business priorities, customer expectations, and internal capacity. * Comfort with ambiguity and willingness to operate strategically and tactically in a fast-paced, evolving environment. * Data-oriented operating style, including the ability to define metrics, track outcomes, identify patterns, and communicate progress clearly. WHAT SUCCESS LOOKS LIKE IN 12 MONTHS * Built credible, responsive relationships with top venture capital firms and ecosystem partners who help connect with high-priority AI-native startups. * Created meaningful engagements with top-tier AI startup founders and established repeatable paths for moving priority startups toward Snowflake adoption and growth. * Led or supported scaled events and ecosystem programs that drive quality customer engagements, founder participation, and actionable follow-up. * Demonstrated innovative ideas for creating campaigns, events or business development programs that address evolving technology trends or unmet startup needs. * Created a trusted operating rhythm with Sales, Marketing, Product, AI Partnerships, Venture, Solutions Engineering, Finance, and Sales Operations. Reports to Head, Snowflake Startups Additional Details: Hybrid Role: In office 3x per week in Menlo Park, CA Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com

Corporate Counsel 2 - Product

Snowflake

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake's Product Legal team is hiring a Corporate Counsel II to support Snowflake's AI Forward Deployed Engineering, AI Governance, Data Clean Rooms, and Native Apps product surfaces. We're looking for a thoughtful, business-minded lawyer who is energized by open-ended problems. You'll report to a Senior Corporate Counsel within Product Legal. RESPONSIBILITIES * Day-to-day product counseling for AI Governance, Data Clean Rooms, and Native Apps. Collaborate with PMs and engineers as features get scoped and built, diving deep on feature functionality, identifying what risks they introduce, and designing meaningful risk mitigations and compliance strategies. Advise on issues relating to IP, privacy, regulatory, contract architecture, and product policy, often at the same time. * Manage AI Forward Deployed Engineering engagements. Support commercial negotiations and drive cross-functional alignment with tax, accounting, finance, product, and engineering stakeholders. Comfort with novel commercial agreements matters here. * Draft and maintain customer-facing legal terms tied to new product offerings and launches. * Discover new best practices for product counseling in the AI era by reimagining how legal work can be done. REQUIREMENTS * Equivalent of 3+ years substantive post-bar legal practice, with substantive practice in one or more of the following: privacy / cybersecurity regulatory, tech transactions, AI/ML regulatory, IP (transactional or litigation), commercial litigation with technology clients, or hybrid commercial-regulatory practice. Your career arc should signal substantive curiosity and adaptability across areas — we care more about how you think and learn than about which practice group you sit in today. * Demonstrated comfort with technical product material — you should be able to read an architecture document and have a focused conversation with Engineering. * Strong judgment under ambiguity. * Clear written communication, especially translating legal positions into plain-English for sophisticated non-lawyer audiences. * Experimental mindset toward AI tooling: curiosity about emerging capabilities, willingness to test, and developed views on what works and what doesn't. AI tooling is part of how the team works day to day; that should sound like a feature of the role to you, not a hurdle. * Integrity, empathy, strategic thinking, and service orientation. * Active California bar OR active bar in another US jurisdiction with eligibility to register as in-house counsel in California. PREFERRED EXPERIENCE (one or more) * Custom enterprise deal experience, particularly technology transactions. * Active practice using AI tools (Cortex, Claude, ChatGPT, GitHub Copilot, or comparable) for legal work product. * Exposure to AI/ML product law: model licensing, data rights, AI Act and state AI laws, customer AI risk allocation. * Exposure to clean-room / multi-party data collaboration, marketplace, app distribution, or AI governance. * Substantive prior career before law school (e.g., teaching, military, government, healthcare, prior tech IC role, policy/advocacy, journalism). * Technical or quantitative academic background prior to law school. INTERVIEW PROCESS The complete interview process will include both remote and in-person interviews, as well as a structured in-office working session and reference checks. The working session will involve redlining a partnership integration agreement excerpt using AI tooling, defending the redline in a stakeholder simulation, walking through how the structure adapts when the partnership layers into a custom AI forward-deployed engineering engagement, and a brief feedback and reflection session. Working-session materials will be shared 48 hours in advance. Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com