Applied Scientist, Demand Forecasting
Workplace: Stockholm, Sweden
Expires: July 31, 2025
An Applied Scientist at Wolt designs and deploys machine learning and applied science solutions to tackle complex business challenges. They work on developing algorithms and data-driven products such as demand forecasting and inventory optimization, collaborating closely across teams to enhance retail inventory processes, improve customer experience, and increase procurement efficiency.
Main requirements:
- Strong passion for data science and applied science to drive business results
- Expertise in building production-ready machine learning solutions
- Strong foundations in machine learning and statistics, especially time-series data and Bayesian methods
- Proficiency in production-level Python coding and working knowledge of SQL
- Ability or willingness to learn productionalization tools such as Flyte, Docker, and AWS
- Clear communication skills to explain technical concepts to non-technical stakeholders
- Excellent analytical problem-solving skills oriented towards business impact
- Good understanding of experimental design and analysis
- Experience or knowledge in procurement and supply-chain optimization, especially in fresh items and retail
Responsibilities:
- Identify high-value opportunities within the product team for applied science solutions
- Develop, prototype, and deploy machine learning and statistical models in production
- Collaborate with software engineers, product managers, designers, and analysts to create data-driven tools
- Work on demand forecasting, inventory optimization, and generating merchant insights
- Continuously improve deployed solutions ensuring measurable business impact
Required hard skills:
- Machine learning and applied statistics, including time-series forecasting and Bayesian methods
- Production-grade Python programming
- SQL
- Experience or willingness to use ML tooling such as Flyte, Docker, MLflow, Seldon Core, and AWS
Recommended hard skills:
- Operations research
- Experimental design and analysis methods
- Knowledge of procurement and supply chain management processes
Soft skills:
- Problem solving
- Clear and effective communication
- Collaborative teamwork
- Analytical thinking
- Adaptability and willingness to learn
Coding languages:
- Python
- SQL
Frameworks:
- Flyte
- MLflow
- Seldon Core
- Docker
Natural languages:
- English (Proficient)
Cultural skills:
- Cross-functional collaboration
- Innovation and experimentation culture
- Agile product development