About the Role:

We are looking for a Senior Data Scientist with strong expertise in Retail Demand Forecasting and Supply Chain Analytics. In this role, you will design and implement advanced machine learning and statistical models to improve forecasting accuracy and enable intelligent decision-making for global retail organizations.

You will collaborate with cross-functional teams including clients, solution architects, consultants, and data engineers to build scalable AI/ML solutions that drive measurable business impact.

What You'll Do:

- Apply a variety of machine learning and statistical techniques such as clustering, regression, ensemble learning, neural networks, time series forecasting, and optimization models.

- Develop and optimize demand sensing and demand forecasting models using techniques such as heuristic models, ARIMA, Prophet, exponential smoothing, and custom approaches.

- Build advanced analytics solutions for optimization (LP, GA, heuristics), anomaly detection, simulation, stochastic modeling, and market intelligence.

- Leverage the latest advancements in AI and machine learning to solve complex business problems.

- Analyze complex datasets, evaluate alternative analytical approaches, and clearly articulate recommendations with underlying assumptions.

- Work with business metrics such as Forecast Accuracy, Bias, MAPE, and develop new performance metrics when required.

- Develop modules and APIs for real-time integration with external systems via web services.

- Collaborate closely with clients, project managers, solution architects, consultants, and data engineers to ensure successful project delivery.

What You'll Bring:

Experience:

- 4+ years of experience in time series forecasting at scale, preferably in retail or supply chain domains.

- Hands-on experience with hierarchical forecasting and heuristic-based best-fit models using algorithms such as ARIMA, Prophet, and exponential smoothing.

- Experience in applied analytics within supply chain planning, including demand planning, supply planning, market intelligence, inventory optimization, and pricing strategies.

Education:

- Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, Engineering, or related field.

Technical Skills:

- Proficiency in Python and/or R for data science and machine learning.

- Deep knowledge of statistical modeling and machine learning algorithms.

- Experience in feature engineering, model tuning, validation, and building scalable ML frameworks.

- Ability to identify and collect relevant input data for model development.

Professional Skills:

- Strong analytical thinking and problem-solving skills.

- Excellent communication and presentation skills.

- Ability to work independently while collaborating effectively in team environments.

Team Culture

We value transparency, open communication, and strong team collaboration. At o9, teamwork goes beyond hierarchy, geography, and functions.

Nice to Have:

- Experience with SQL, databases, and ETL tools.

- Exposure to distributed computing technologies such as Hadoop, Hive, Spark, MapReduce, or optimization tools like Gurobi.

- Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.

- Experience implementing planning or supply chain applications.

- Understanding of supply chain concepts and retail planning processes.

- Master's degree in Computer Science, Applied Mathematics, Statistics, Engineering, Business Analytics, Operations, or related fields.

What We Offer:

- Competitive compensation with stock options for eligible candidates.

- Flat organization structure with a strong entrepreneurial culture and minimal corporate politics.

- Opportunity to work with highly talented teams solving complex global supply chain challenges.

- Opportunities for onsite travel during key project phases.

- A strong learning environment with continuous mentorship and collaboration.

- A diverse and inclusive international workplace culture.

- A strong focus on work-life balance and employee well-being.

Work-Life Balance: https://youtu.be/IHSZeUPATBA?feature=shared

Feel Part of a Team: https://youtu.be/QbjtgaCyhes?feature=shared