Forecast engine utility (FEU) is Unilever's in-house AI/ML based demand & promotion forecasting solution. Senior Data Scientist (Innovation) role under FEU will be responsible for research and development of state of art large scale demand forecasting and promotion planning algorithms. Objective of this role is to improve forecast KPIs globally via scalable ML/AI methods. Key Responsibility of this role will be to develop innovative machine learning solutions for large scale demand forecasting solutions. These innovative ML models will have potential to scale across all Unilever markets (100+ countries).
Who You Are and What You'll Do
- Execute data science innovation topics for Forecast Engine Utility and Integrated Business operations to deliver global forecast KPIs
- Research and develop algorithms/Model to improve large scale demand forecasting problem (+billions of timeseries). Build, maintain, and improve new and existing suite of algorithms and their underlying systems.
- Create technical design; innovative problem solving, Document and Develop technical solutions aligned with business objectives; identify gaps between the current and desired end-states
- Analyzing the AI/ML algorithms that could be used to solve a given problem and ranking them by their success probability.
- Engaging in strategic discussions to identify problems while measuring and improving the quality of workflows. Identify and implement opportunities to improve tooling and implementation of scalable solutions
- Actively contribute to and re-use UL DS community best practices.
- Contribute to the AI innovation and build thought leadership via publications/patents and presence in industry/academic conference. Further, actively contribute towards establishing innovation team as thought leader in demand forecasting within the CPG industry.
- Working in an agile environment with globally distributed teams.
- Mentor and supervise team member across the organization.
- Write efficient and well-organized ML based software to ship products in an iterative, continual-release environment.
- Engaging in strategic discussions to identify problems while measuring and improving the quality of workflows. Identify and implement opportunities to improve tooling and implementation of scalable solutions
- Working in an agile environment with globally distributed teams.
What You Need to Succeed
- 5+ years of relevant experience with skills in Time Series models, Machine Learning, and strong hold of object-oriented programming with large data.
- Experience in enterprise level ML product development is required.
- Bachelor's Degree required