Senior GTM Data Scientist

About Stripe

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.

About the team

We are looking for a Senior Data Scientist to join our Global GTM Target Setting Competency Hub. This central analytics team plays a pivotal role in supporting Stripe’s Go-To-Market (GTM) and Marketing organizations. Our team collaborates with Finance & Strategy (F&S), Global Planning, Marketing Operations and our wider GTM Revenue Data Science team to align the Go-To-Market teams towards common goals, fostering a culture of accountability and empowering informed decision-making. 

As a Senior Data Scientist, you will be at the forefront of shaping Stripe's commercial ambitions. You won't just be analyzing data; you'll be architecting the future of our target-setting frameworks, directly influencing resource allocation, strategic planning, and ultimately, Stripe's success. In today’s rapidly evolving market, maintaining target setting integrity and fostering innovation are crucial for sustained success.  

Key Responsibilities

• Goal Setting: Collaborate closely with leadership and cross-functional teams to establish data-driven goals and performance metrics that align with overall business objectives. Your expertise in target setting will be crucial to translating strategic goals into measurable and achievable targets at all levels of the organization.
• Forecasting & Modeling: Design and implement sophisticated predictive models and tools for sales forecasting and creating dynamic target allocation systems ensuring the connectivity of metrics throughout the sales funnel. Proactively identify opportunities for innovation in target setting, leveraging cutting-edge data science techniques and industry best practices. Lead the design and execution of rigorous experiments to evaluate the effectiveness of different target-setting methodologies and drive continuous improvement.
• Communication of complexity: Develop compelling data visualizations and narratives to communicate complex findings and recommendations to both technical and non-technical audiences, including executive leadership. Our predictive models need to be understandable and credible to stakeholders, including business leaders, sales teams, and marketing teams.  Oversee implementation of enabling systems and tools, working closely with internal systems teams communicate goals and progress towards goals clearly for the wider organisation. 
• Process, Policy and Tooling: Contribute to foundational principles and policies on how we measure success of teams and individuals.  Define and prioritize the development of tools and platforms that streamline the target-setting and target cascade process,  and  facilitate more data-driven decision-making in the process. 
• Metric design: Utilize statistical techniques to assess scenarios and quantify the potential impact of business outcomes on metric design and attainment distributions. 
• Growth Analytics Innovation: Lead or contribute to exploratory initiatives aimed at uncovering new and innovative ways to leverage data science for driving Stripe's growth including in the optimisation of territory design. Engage in research and experimentation with cutting-edge analytical techniques, exploring new data sources, and developing novel approaches to target setting and performance management.  Stay abreast of the latest advancements in data science, machine learning, and the SaaS industry to ensure Stripe remains at the forefront of analytical capabilities.
• Mentorship: Act as a mentor to junior data scientists and analysts, sharing best practices in data analysis, goal management, and modeling techniques to enhance team capabilities and foster professional growth.

Required Skills and Qualifications

• Master’s degree or PhD in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 8+ years of experience in data science  partnering with business functions such as Revenue Operations, Finance, Growth, Marketing, preferably within the tech or financial services industry. You have a proven track record of independently leading go-to-market data science projects from problem definition to impactful busines