Data Scientist, Integrated Business Planning

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Agilent Technologies

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1999

🔬 Science

🧬 Biotechnology

💊 Pharmaceuticals

💰 $500M Post-IPO Debt on 2019-09

Science • Biotechnology • Pharmaceuticals

Agilent Technologies is a global leader in the field of analytical and laboratory instruments. The company offers a diverse range of products and solutions, including gas and liquid chromatography, mass spectrometry, lab supplies, and software and informatics. Agilent serves various industries, such as biopharma, food and beverage testing, clinical diagnostics, and environmental testing. Additionally, Agilent provides comprehensive services for lab management, maintenance, and instrument repair. They focus heavily on advancing science through sustainable solutions and supporting genomics, pathology, and cancer research with advanced technologies.

📋 Description

• Provide data-driven insights, dashboards, and scenario modeling to support demand and supply planners, S&OE/S&OP processes, and enterprise decision-making • Drive continuous improvement in analytics, data quality, and model reliability • Drive automation and advanced analytics, leveraging Python, SQL, and BI tools to scale insights • Partner with more senior team members to align analytics with standards, governance, and process maturity efforts • Generate dashboards and KPIs that support IBP governance and forum discussions • Enable S&OE/S&OP with near-term supply-demand coverage analytics, including early warning indicators

🎯 Requirements

• Bachelor's or Master's Degree or equivalent in data science, statistics, computer science, or related field. • Post-graduate, certification, and/or license are a plus. • Ability to work independently and as part of a team in a fast-paced environment. • Knowledge in predictive modeling, machine learning, and statistical analysis preferred. • Programming languages such as Python, R, or SQL. • Data visualization tools like Tableau, Power BI, Qlik, Spotfire or similar. • Strong analytical and problem-solving skills with the ability to interpret complex data. • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. • Knowledge of advanced machine learning techniques and frameworks.

🏖️ Benefits

• Remote work options