About the Role

What You'll Do

• Design, build, validate, and deploy end-to-end predictive models, machine learning, and mathematical optimization solutions in cloud environments

• Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various needs

• Develop and implement data-driven models to improve inventory management, reduce excess stock, and prevent stockouts.

• Communicate meaningful, actionable insights from large data and metadata sources to stakeholders to drive strategic adoption

• Collaborate with data engineering and IT teams to ensure data accessibility, integrity, and scalability for analytics and modeling purposes

• Continuously monitor and refine existing models to ensure accuracy and relevance, and provide recommendations for improvement.

• Integrate emerging methodology, technology, coding and other best practices that to the team and create effective documentation.

Who You Are

• Proven experience in machine learning, statistical modeling, experimental design, operations research, inventory theory and a track record for creating tangible business impact

• Proficiency in building end-to-end models and deploying them in cloud environments

• Strong programming skills in Python, SQL, PySpark or similar languages.

• Excellent problem-solving skills with the ability to translate complex data into actionable business insights.

• Strong communication and stakeholder management skills, with the ability to convey technical information to non-technical stakeholders clearly and effectively and a demonstrated appetite for relationship building

• Skills to collaborate with cross-functional teams and influence product and analytics roadmap

• Bachelor’s and/or Advanced degree in Data Science, Operations Research, Statistics, Math, Computer Science, Industrial Engineering or related field preferred