Supply Chain Data Scientist

The purpose of this role is practical application of data science in supply chain planning and inventory management to improve underlaying processes and deliver financial value.

To succeed in this role, you must have multidisciplinary skill set - proven experience in project management and SC planning, knowledge of planning systems (SAP APO/IBP, OM Partners or similar), SAP architecture (underlying tables, transactions) and strong technical and analytical skills.

In this creative role you will have unique opportunity to collaborate with various stakeholders in the global organization working on various improvement initiatives, development of analytical tools, optimization models or supply chain simulations and you need to feel comfortable in each stage of this process (design, develop and deploy) to thrive and succeed.

You are self-starter with hands-on approach and continues improvement mindset working on your own initiative under moderate supervision. You know how to source and use data together with statistical methods and technology to improve processes. It is important you have theoretical knowledge but more important you understand how to use it in practice to add value.

Your nearest assignments will focus on portfolio segmentation, product life cycle management, development of replenishment strategies and inventory optimization within distribution network. All contributing to development of planning tool supporting decision making process for planning teams.

• Degree in Supply Chain Management or APICS CPIM certification and 5-7+ years experience in Global Supply Chain and Inventory Management essential (multi-site, multi-region)
• Degree or certification in Data Science desirable
• Formal Project Management and problem-solving training desirable, e.g., Six Sigma, Lean.

• Demonstrated ability to select and work with appropriate analytical tools and software (Excel, PBI, relevant libraries in R and Python or SQL) and build ETL pipelines
• Demonstrated experience using AI-assisted development and automation tools, such as Codex, to accelerate data analysis, code development, documentation, troubleshooting, and creation of analytical tools while applying appropriate validation and governance
• Ability to critically evaluate AI-generated outputs for accuracy, data quality, business relevance, bias, and operational feasibility before applying them to supply chain planning, inventory optimization, or decision-support processes
• Demonstrated ability to analyze large data sets and visualize findings
• Demonstrated ability to wrangle, cleanse and model data from various sources (SAP, .csv, .xlsx, .txt, .parquet, .rds, data lake etc.)
• Proficient in Excel and Power BI (Power Query/M, DAX, relational database model, data visualization); Power BI Data Analyst Associate certification is a plus
• Knowledge of SQL and R/Python highly desirable
• Experience working with data warehouse/data lake desirable (experience with Snowflake a plus)
• Knowledge of Statistics and Machine Learning or strong willingness to quickly develop in this area
• Demonstrated ability to analyze large data sets and to prioritise actions for maximum impact
• Ability to develop and deploy short-term tools and reporting capabilities (with quantified accuracy and precision) essential
• Solid written and verbal communication skills, experience in a matrix environment desirable

Typically works in an office environment with adequate lighting and ventilation and a normal range of temperature and noise level.

Work assignments are diversified. Examples of past precedent are used to resolve work problems.

Most aspects of work are timebound and fit into a standard reporting cycle based on the monthly financial reporting calendar. There is an ongoing requirement to work to deadlines and to manage competing priorities.

Minimal physical effort is required. Work is mostly sedentary but does require walking, standing, bending, reaching, lifting or carrying objects that typically weigh less than 10 lbs.