Staff Data Scientist

Who we are  At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to  hundreds of thousands of businesses  and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! . See yourself at Twilio Join the team as Twilio’s next Staff Data Scientist. About the job This position is needed to drive growth across the full funnel, with a specific mandate to revolutionize our cross-sell and upsell initiatives. In this role you won't just be building models, you’ll be designing the brain behind our revenue engine. You will bridge the gap between complex data science and actionable business outcomes, turning raw data into high-impact data products. Dive into our growth engine focused on developers around the world who use and love Twilio products and surface high potential opportunities for GTM Sales and Marketing teams. You will be part of a highly visible Data Science & Analytics team that serves as the trusted advisor to stakeholders across the company focused on growth. You will get to work with great minds across Marketing, Sales, Product, and Finance. Responsibilities In this role, you’ll: Translate business objectives into a data science roadmap that prioritizes high-LTV (Lifetime Value) growth Dig into the science of our self-service funnel and graduation to Sales to uncover optimization opportunities, diagnose issues, and provide actionable recommendations through data products Identify leading indicators of revenue and build data science models that surface high potential opportunities Serve as a key technical advisor to GTM leadership across Sales and Marketing Build extensive knowledge of user behavior, the customer purchase and usage experience, and our lead funnel to inform data science solutions Develop sophisticated recommendation engines that identify "next-best-action" opportunities within our existing customer base, ensuring sales and marketing engagement the right person at the right time Build robust frameworks to measure the incremental impact of your data products, moving beyond simple correlation to prove true ROI Leverage machine learning and generative AI capabilities to support Product-led-growth (PLG) initiatives  Partner with Data Engineering to define the long-term roadmap for GTM data architecture, ensuring high-fidelity 'source of truth' data for signals like product-qualified leads (PQLs) Oversee the seamless integration of data products into the daily workflows of stakeholders, ensuring insights are delivered where they work (Slack, CRM, Wiki/Docs, Tableau, email, etc.)  Create documentation, dashboards, reports, and executive summaries for your data products Partner with Sales, Marketing, Enterprise Technology, Product, and Ops teams to bring relevant data science products to life Qualifications  Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: 7+ years in Data Science/ML, with a proven track record in a GTM or Growth environment (SaaS experience preferred) 5+ years of experience with Applied Statistics/Machine Learning or experimentation (i.e. A/B testing) in an industry setting Expert-level proficiency in Python/R, SQL, and modern ML frameworks (Scikit-learn, XGBoost, PyTorch, or TensorFlow) Experience deploying models into production environments and building scalable data pipelines (Airflow, dbt, Spark) Experience initiating and driving projects which leverage Generative AI capabilities to drive productivity and efficiency, preferably in a product or technology organization Strong understanding of GTM metrics: CAC, LTV, ARR, ARPU, Pipeline Velocity, Lead-to-Close ratios, etc. The ability to explain a gradient-boosted tree to a Sales Director and a business strategy to a Data Engineer with equal clarity Desired: A degree in a quantitative field (e.g. statistics, mathematics, physics, econometrics, or computer science) Masters preferred but not required 5+ years of experience doing quantitative analysis at a technology company, consulting firm, investment bank, or product management firm Location A: In o