Senior Data Scientist, Customer Care

Where you’ll work: Remote (US) Engineering at GoTo We’re trailblazers in remote work technology—building powerful, flexible solutions that empower everyone to live their best life, both at work and beyond. With us, you’ll have the opportunity to chart new paths and help redefine how the world works. For us, AI isn’t just a buzzword; it’s a tool we use to deliver real, practical value to our customers and teams. We focus on solving meaningful problems, not just adding features for the sake of using AI. Here, growth takes many forms: you can expand your skills, take on new challenges, lead initiatives, and explore creative ideas. Join a GoTo product team and play a key role in transforming the workplace for millions of users worldwide—your work will truly make a difference. Your Day to Day • Design, build, and own end-to-end machine learning models and AI-powered solutions, from problem framing through production deployment and impact measurement, focused on driving customer retention and operational excellence • Develop and enhance AI-driven tools that deliver explainable, actionable insights to Customer Success and Renewals teams, enabling data-informed decisions that protect and grow revenue • Partner closely with Customer Success, Renewals, Product, and Engineering to translate complex business challenges into well-scoped data science initiatives aligned to high-impact retention opportunities • Evaluate, prototype, and implement emerging AI/ML approaches, including generative AI and agentic workflows, to improve team efficiency and stakeholder value in a rapidly evolving landscape • Mentor and support fellow Data Scientists by setting high standards for analytical rigor, code quality, and documentation while contributing to best practices and team growth What We’re Looking For • 5+ years of experience in data science, machine learning, or a closely related quantitative field, with a proven ability to deliver production-grade solutions • Strong proficiency in Python and SQL, with hands-on experience building, deploying, validating, and monitoring machine learning models in production environments • Deep foundation in statistical modeling, machine learning techniques, and experimental design, with the ability to translate ambiguous business questions into actionable analytical frameworks • Effective written and verbal communication skills, with experience presenting insights to and influencing cross-functional technical and non-technical stakeholders • Curiosity and adaptability in working with emerging AI technologies (such as LLMs, prompt engineering, or RAG), and comfort operating in evolving, fast-moving environments, ideally within SaaS or subscription-based businesses