Supply Chain Data Scientist

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About this opportunity:

The Supply Chain Data Scientist is part of the Hardware Services team and develops data analytics and machine learning solutions that solve business problems in the spare parts management environment. The role combines supply chain understanding, statistical and machine learning expertise, and business application knowledge to strengthen the data foundation, generate actionable insights, support the transformation toward a data-driven supply chain and support supply chain modelling. The role works closely with business stakeholders and analytical communities across Ericsson to translate requirements into practical, scalable solutions.

What you will do:

• Gather, interpret, and analyze supply chain data using statistical and analytical techniques, and translate findings into valuable business insights and visualizations.

•Assess data sources and work with the business to collect, clean, preprocess, define, improve, and manage data for analytical use.

•Develop and implement analytical and machine learning solutions, including predictive models, recommendation engines, anomaly detection, statistical models, and other relevant advanced analytics capabilities.

•Help advance the analytics capability toward predictive, prescriptive, and increasingly automated or algorithmic decision support.

•Apply programming and data technologies such as Python and SQL, in line with the needs of the solution and current market practices.

•Communicate key findings and recommendations clearly to business stakeholders and senior management through verbal, visual, and written media.

•Support the transformation toward a data-driven organization and a stronger data culture within Hardware Services.

•Explore relevant developments in data science, analytics, and artificial intelligence and apply them to Hardware Services business challenges.

•Mentor colleagues in the role discipline and share practical knowledge within the team.

The skills you bring:

• •Supply chain and business understanding, preferably including spare parts management or service supply chains.
• •Strong analytical skills, statistics, and the ability to organize, analyze, and present significant amounts of data accurately.
• •Data preprocessing, data management, and data quality improvement.
• •Machine learning algorithms and artificial intelligence systems.
• •Open-source programming languages and analytical technologies, including Python and SQL.

•Bachelor's degree in Computer Science, Mathematics, Statistics, Supply Chain Management, Logistics Management, or a related quantitative field.

• •5 to 8 years of relevant industry experience.
• •Demonstrated experience in data analysis, statistical modelling, or machine learning.
• •Experience as a data analyst or data scientist in a supply chain environment, preferably related to spare parts management.
• •Hands-on experience building and implementing machine learning models.
• •Experience with cloud-based machine learning solutions.