Data Scientist (Ref: 197473)

Founded in 1979, This organisation International, Inc. stocks and sells New and Surplus Industrial Automation, MRO, Pneumatic, Motion, Electronic, Hydraulic, HVAC and Electrical Control Equipment for plant floor and facilities maintenance machinery. This organisation is headquartered in Willingboro, New Jersey.

Bring applied analytics and statistical thinking to problems that directly affect supply, inventory and customer service performance. In this role you will own end-to-end data science initiatives: frame questions with commercial and operational stakeholders, prototype predictive models and analytics, and translate results into dashboards and operational processes that reduce lead times and improve parts availability. Expect to improve forecasting for slow-moving and surplus items, detect and prioritise parts at risk of stockouts, and quantify the impact of pricing and sourcing choices on margin and service. Your work will influence buying decisions, warehousing priorities and customer fulfilment practices across the organisation.

• Develop and maintain forecasting and predictive models for demand, lead time and stockout risk.
• Build analytics and visualisations that make model outputs actionable for buyers, warehouse managers and sales teams.
• Collaborate with procurement, operations and sales to translate analytical insights into replenishment rules and process changes.
• Design experiments and A/B tests to evaluate pricing, sourcing or stocking policy changes.
• Prepare clear documentation and present technical findings to non-technical stakeholders to drive adoption.
• Validate and monitor model performance, implementing retraining and data-quality checks as needed.
• Work with engineers or IT to productionise models and integrate outputs into existing data pipelines and business systems.

• Bachelor's degree in a quantitative field or equivalent work experience.
• Experience building and evaluating forecasting and machine-learning models.
• Proficiency in Python or R and experience with pandas, scikit-learn or equivalent libraries.
• Practical experience with data visualisation tools (for example, Tableau, Power BI or similar).
• Strong data-wrangling skills and familiarity with SQL for extracting and shaping transactional and inventory data.
• Ability to communicate technical findings to commercial and operational stakeholders.
• Preferred: experience with time-series methods for intermittent demand, inventory optimisation or supply-chain analytics.

• A competitive compensation package appropriate to the role.
• Opportunities for professional development and career growth.
• The opportunity to work on meaningful projects with visible organisational impact.
• Access to the tools, systems, and resources needed to perform the role effectively.

This role offers a chance to shape how the organisation buys, stores and supplies critical parts to manufacturing and facilities customers. Candidates with relevant supply-chain, retail or industrial distribution analytics experience are encouraged to apply; transferable experience from related domains will be welcomed.