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通用磨坊股份有限公司

Senior Analyst - Supply Chain Advanced Analytics

Data & ML

Employment

Not stated

Level

Senior

Category

Data & ML
Not doable from Austria

Country assessment

Not doable from Austria because it is tied to an office and never says it can be done remotely.

Working conditions

Working hours: This role requires you to operate in 1.30 pm to 10.30 pm shift.

Our assessment is guidance. Confirm arrangements with the employer.

Skills mentioned in this posting

PythonML/AI

Job description

COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together.

Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.​ OVERVIEW In this role, the Senior Analyst key responsibilities involve leveraging data science to solve supply chain challenges. This includes data analysis, model development (descriptive, diagnostic, predictive, prescriptive), and scenario planning.

Focus to improve modelling efficiency through automation and mentor junior analysts. Finally, independently manage moderately complex projects to deliver timely and impactful solutions. This role requires you to operate in 1.30 pm to 10.30 pm shift. KEY ACCOUNTABILITIES Translate supply chain business objectives into analytical scope, assess data feasibility, and define success criteria.

Cleanse and explore data to identify trends and root causes, then develop statistical, optimization, or machine learning models. Conduct scenario planning and sensitivity analysis while independently managing moderately complex analytical projects to deliver impactful solutions. Improve modelling efficiency through automation, eliminate redundant workflows, and mentor analysts by validating analytical deliverables.

Domain Expertise Plan : Supply and production planning; capacity, demand, and inventory planning; make-versus-buy decisions; service-level optimization and cost trade-offs. Source : Procurement process optimization; cost-saving and efficiency opportunities; financial, geopolitical, and environmental, social, and governance risk assessment; supplier sustainability and carbon-footprint tracking.

Manufacturing and Engineering (MaKE) : Manufacturing performance improvement and waste reduction; failure-mode analysis; anomaly detection; predictive maintenance; root-cause analysis; predictive and prescriptive downtime reduction. Network : Network design and distribution; facility location; greenfield and brownfield analysis; transportation and logistics planning; route optimization; cross-docking; push, pull, and postponement replenishment strategies.

End-to-End & Operating Unit : Understanding of the Plan, Make, Source, and Deliver pillars; ability to connect cross-functional priorities; holistic solution mindset; awareness of key supply chain metrics, including service, cost of goods sold, and waste. MINIMUM

QUALIFICATIONS

Education: Bachelor’s degree from accredited university (Full Time) in Business Analytics, engineering, statistics or a related quantitative field. Experience: 3+ years of related experience in Supply chain analytics Technical Skills: Any optimization tool like Supply Chain Guru/Optilogic/Any logic (Nice to have) Python, Dash or similar visualization tools, SQL, and cloud platforms such as BigQuery Knowledge of statistical modeling, optimization, machine learning Proficiency in Excel and PowerPoint, leveraging advanced functions for data analysis, visualization, and effective business storytelling PREFERRED

QUALIFICATIONS

Post graduation in Industrial Engineering, statistics or Supply Chain operations Professional Certifications for supply chain and Data science ELIGIBILITY Applicants must meet minimum age qualifications in the country in which the job is located.