Staff Data Scientist

OverviewUdemy is an AI-powered skills acceleration platform helping people and teams grow. Our mission is to transform lives through learning. We serve over 80 million learners and 17,000 businesses. This is an in-office position requiring three days a week in the office (Tuesday, Wednesday, Thursday) with flexibility on Mondays and Fridays.About this roleIn the Data organization at Udemy, we seek collaborative, self-motivated data scientists to join our Product Analytics team. You will design, build, and maintain production data systems that power Udemy's most impactful machine learning products. You will collaborate with data scientists, product managers, engineers, and marketers to deliver robust, data-driven solutions. This role combines software engineering and data science expertise with strong communication and a passion for turning complex challenges into business impact.What you'll be doingArchitect and develop intelligent, scalable analytics services, including user segmentation, forecasting, and dynamic pricing, used across product and business teams.Collaborate cross-functionally to define requirements for ML-driven systems, translate business goals into technical designs.Lead development and scaling of modular ML components (data pipelines, workflows, evaluation, monitoring, retraining) to ensure reliable services.Raise standards for code quality, data hygiene, reproducibility, and infrastructure for analytics-centric ML systems.Mentor and upskill team members on advanced ML concepts and software engineering practices.Advise on the lifecycle of ML services within Product Analytics and shape long-term roadmap for leveraging advanced analytics.What you'll haveProven expertise in architecting, developing, and deploying ML solutions (e.g., segmentation, forecasting, pricing) bridging research and production.7+ years of professional experience in data science or applied ML with leadership in modular ML system development.Deep fluency in Python and SQL; hands-on experience with ML and data engineering libraries (e.g., scikit-learn, pandas, PySpark, MLflow, Airflow).Track record of designing pragmatic, scalable architectures for ML-powered analytics services (not necessarily full microservices).Strong understanding of the ML lifecycle: data ingestion, feature engineering, model development, evaluation, deployment, monitoring.Expertise in MLOps including reproducibility, testing, CI/CD, monitoring, and governance.Exceptional communication skills enabling collaboration with data scientists, engineers, PMs, FP&A, and marketing.Strong business judgment to understand product and business drivers for analytics-based ML services.Experience mentoring data scientists and establishing shared coding, modeling, and service standards.Experience designing, running, and interpreting A/B tests and statistical evaluations in a business setting.Ability to operate autonomously, prioritize, and influence as a senior technical leader within Product Analytics.Deep understanding of causal inference problems.Why work here?You'll grow here. Access Udemy courses, a monthly UDay, and a personal budget for self-improvement.AI is real here. Practical application of AI in how we learn and work, with space to experiment.You'll own your work. Lead and follow through with minimal permission chains.You'll build with others. Open collaboration where every voice is welcomed.You'll see your impact. Your work helps people grow their skills and careers.Bring your curiosity. We'll provide the platform and support. Let's LEARN together.Benefits and diversityBenefits start with you and vary by region. Refer to region-specific benefits pages (Australia, India, Ireland, Mexico, Turkiye, US) for details. All benefits are subject to change in accordance with policy and law. Udemy values diversity and inclusion; qualified applicants are considered without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital status, veteran status, medical condition, or disability. We welcome applicants of varied backgrounds.Data privacy information is available within the Udemy Careers Privacy Notice. #J-18808-Ljbffr

Created: 2025-09-17