Lead Supply Chain Data Scientist

Transforming the Future of Enterprise Planning

At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions—even billions—in value leakage, we help businesses plan smarter and faster.

This not only enhances operational efficiency but also reduces waste, leading to better outcomes for both businesses and the planet. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains.

About the role:

o9 Solutions is looking for an experienced, talented, and motivated Lead Data Scientist to come join our global team. As part of this Data Science team, you will be involved in the end-to-end delivery of our supply chain planning products and building advanced forecasting models with Predictive Analytics, Machine Learning and AI with algorithms such as R, and Python. These models will have used cases for Demand Planning, Supply Planning, Market Mix Modeling, Price Elasticity, New Product Planning, Store Assortment, Market Optimization, and more.

You will be key in understanding the customers supply chain problems, designing solutions, developing, and deploying models, validating, and maintaining those models.

A successful candidate will bring a Master’s in Computer Science, Mathematics, Statistics, Economics, Engineering, and 5+ years of experience in hands-on modeling in R or Python, in a supply chain forecasting capacity. You will enjoy working directly with customers and our larger o9 Data Science team.

What you’ll do for us:

• Research, design, build, deploy, and validate new and existing machine learning models and predictive analytics for advanced forecasting in supply chain demand planning that will drive our customers growth from insights that are allow for better decision making
• Apply a variety of machine learning techniques (clustering, regression, neural nets, time series, optimizations etc.) to their real-world advantages/drawbacks for insights internally and externally
• Collaborate with solution architects, business operations specialists, engineers, data scientists, product managers, and internal/external business teams to make sure the models are aligned with business objectives and customer needs
• Develop machine learning models for segmentation and optimization
• Provide visualization of complex data sets that includes mathematical models, algorithms, and robust analytics
• Produce recommendations and use statistical techniques that answer key product questions
• Provide on-going support for development of demand planning forecasting and predictive analysis.
• Be a storyteller to explain the “why and how’” of your data driven recommendations to cross-functional teams and customers
• Guide junior data scientists and oversee their activities to ensure proper alignment/execution of their activities, and maintain high coding standards and best practices within organization

What you’ll bring:

• Experience: 5+ years of data science and data analytics experience.
• 5+ years’ experience in supply chain planning analysis that specialize in: Demand Planning, Predictive Analysis, Demand Forecasting, Supply Planning, Inventory Market Optimization, Store Segmentation, Market Mix Optimization, New Product Planning, or similar.
• Experience in building scalable ML frameworks for demand sensing including identifying and collecting relevant input data, feature engineering, tuning, and testing.
• Experience developing experimental and analytics plans for data modeling processes with the ability to accurately determine and resolve problems
• Experience gathering data requirements for statistical predictive analytics research that drives market research, product innovation, and implementation in a supply chain space
• Strong presentation and communications skills with ability to communicate complex analytical or technical concepts to audiences with limited analytical or technical background
• Experience in time series forecasting in scale using heuristic based hierarchical best-fit models using algorithms like exponential smoothing, ARIMA, prophet and custom parameter tuning
• Education: Master’s in Computer Science, Mathematics, Statistics, Economics, Engineering, or related field
• Skills: R, Python, Pyspark, Machine Learning, SQL, building models in platforms like Power BI or Tableau
• Characteristics: You thrive in a fast paced, challenging environment, where this is much white space and problem solving is at the heart of what drives your analysis
• We really value team spirit: Transparency and frequent communication is key. At o9, this is not limited by hierarchy, distance, or function

Preferred Experience…

• Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies
• Experience with Deep Learning frameworks such as Keras, Tensorflow or PyTorch is preferable
• Experience in implementing planning applications will be a plus