Principal Data Scientist - 11771

• Pioneering Technology: At Coupa, we're at the forefront of innovation, leveraging the latest technology to empower our customers with greater efficiency and visibility in their spend.
• Collaborative Culture: We value collaboration and teamwork, and our culture is driven by transparency, openness, and a shared commitment to excellence.
• Global Impact: Join a company where your work has a global, measurable impact on our clients, the business, and each other. 

What You’ll Do

• Technical & Strategic Leadership: Define and drive the long-term technical roadmap for applied Machine Learning within the Supply Chain and Sourcing domains, ensuring alignment with broad product and engineering goals.
• Hybrid ML/OR Systems: Partner deeply with the Operations Research team. Design and build robust predictive models (e.g., demand forecasting, lead-time estimation, supplier risk scoring) that act as direct, high-quality inputs into downstream mathematical optimization algorithms.
• Advanced Model Development: Research, prototype, and deploy state-of-the-art machine learning models (Time Series Forecasting, Deep Learning, NLP, and GenAI) to extract actionable insights from massive, messy, and complex global supply chain datasets.
• MLOps & Scalability: Architect highly scalable data pipelines and ML infrastructure. Work closely with software engineers to deploy models into a high-throughput, multi-tenant SaaS environment, ensuring robust model monitoring and lifecycle management.
• Mentorship & Culture: Serve as the chief technical mentor for the Data Science team. Elevate the team's capabilities through rigorous code reviews, algorithmic design sessions, and championing best practices in data science.
• Cross-Functional Influence: Translate highly ambiguous business problems into structured data science projects. Communicate complex ML concepts, limitations, and trade-offs to non-technical executives, product managers, and key enterprise customers.

What You Will Bring to Coupa

• Ph.D. or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a closely related quantitative field.
• 8+ years of industry experience building and deploying machine learning models in a commercial software environment.
• Deep expertise in predictive modeling, time-series forecasting, statistical analysis, and modern machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch, XGBoost).
• Production-grade programming proficiency in Python, as well as advanced skills in SQL and data manipulation.
• Proven track record of leading complex, multi-quarter ML initiatives and successfully deploying models that drive measurable business impact.
• Strong architectural understanding of integrating Machine Learning systems with downstream software services.
• Excellent executive-level communication skills, with the ability to explain complex statistical concepts to diverse audiences.
• You are a deeply technical ML expert who thinks holistically about end-to-end AI systems, particularly how predictive signals can drive downstream decision-making and optimization.
• You are comfortable operating in a high-autonomy environment, taking concepts from white-board theory to production-grade software.
• You are a force multiplier who loves mentoring others and elevating the engineering and scientific rigor of the entire organization.
• You embody Coupa’s core values: Ensure Customer Success, Focus on Results, and Strive for Excellence.

• What Will Give You a Competitive Edge (Preferred Qualifications)

• Domain expertise in Supply Chain Management, Logistics, Demand Planning, or Strategic Sourcing.
• Familiarity with Operations Research concepts (e.g., Linear Programming, Heuristics) and experience building hybrid systems where ML outputs feed into optimization solvers (like Gurobi or CPLEX).
• Experience with Big Data technologies and distributed computing frameworks in the Hadoop/Spark ecosystem (e.g., PySpark, Databricks).
• Hands-on experience with cloud-native ML infrastructure (AWS SageMaker, Bedrock, containerization via Docker/Kubernetes).
• Experience applying Large Language Models (LLMs) and Generative AI to unstructured enterprise data.