Data Scientist

JR Spain; Badajoz; Presencial; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

A leading company in the field is seeking a Remote Data Scientist specializing in Supply Chain Optimization. This 12-month freelance contract offers an opportunity to develop predictive models, analyze data, and drive efficiency across supply chain operations. Ideal candidates will have experience in data science, network modeling, and proficiency with Python and SQL. Join a dynamic team and contribute to innovative solutions that optimize global supply chains.

Formación

• Proven experience in data science for supply chain/logistics, particularly in network modeling and optimization.
• Hands-on knowledge of mathematical optimization techniques (especially MILP) and heuristic design.
• Strong background in Python, SQL, and modeling tools.

Responsabilidades

• Lead the full lifecycle of supply chain network modeling, detecting anomalies, and developing predictive models.
• Normalize and cleanse historical supply chain data, conduct root cause analysis, and monitor KPIs.

Conocimientos

Data Science

Supply Chain Analytics

Mathematical Optimization

Python

SQL

Heuristic Design

Azure Cloud

Herramientas

Coupa

Llamasoft

Descripción del empleo

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Data Scientist – Supply Chain Optimization

Location: Barcelona, Spain (Remote)

Contract: 12-month Freelance (Open to Permanent)

We are seeking a Data Scientist with deep expertise in Supply Chain Optimization to join our team on a remote freelance basis (based in Spain). This is a 12-month contract with the potential for a permanent role. You will be at the intersection of data science and supply chain strategy, building intelligent solutions to optimize global operations and drive actionable insights from complex datasets.

Key Responsibilities:

1. Network Design & Modeling: Lead the full lifecycle of supply chain network modeling—from raw data ingestion to model deployment using tools like Coupa or Llamasoft. Detect and correct anomalies in capacity, throughput, and transportation cost data. Develop predictive models to fill in missing data and forecast new routes. Automate scenario generation (e.g., warehouse optimization, opening/closing decisions) for scalable, dynamic use cases. Connect and unify multiple isolated supply chain models. Design and implement advanced mixed-integer linear programming (MILP) optimization models. Build heuristics to accelerate complex NP-hard problems, reducing runtime from days to hours. Enable background automation of hundreds of models to continuously identify optimization opportunities.
2. Supply Chain Analytics & Insights: Normalize and cleanse historical supply chain data (3–5 years), accounting for disruptions like strikes or anomalies. Conduct root cause analysis to understand deviations between actual operations and planned models. Identify and diagnose bottlenecks across the supply chain. Discover non-obvious patterns and interdependencies (e.g., promotional events in one region affecting inventory in another). Monitor KPIs and trends to detect performance drift or abnormal activity, using statistical and machine learning methods. Bring a creative, data-driven approach to uncover hidden correlations and systemic inefficiencies.

What We're Looking For:

• Proven experience in data science for supply chain/logistics, particularly in network modeling and optimization.
• Hands-on knowledge of mathematical optimization techniques (especially MILP) and heuristic design.
• Strong background in Python, SQL, and modeling tools (e.g., Coupa, Llamasoft).
• Ability to work with messy, incomplete, and large-scale data.
• Creative thinker with a problem-solving mindset and strong business intuition.
• Azure Cloud experience is a plus.