Data Scientist

JR Spain; Priego de Córdoba; A distancia; EUR 50.000 - 70.000; A tiempo parcial

Descripción de la vacante

A dynamic logistics firm is seeking a Data Scientist specializing in Supply Chain Optimization to join as a remote freelancer. The role involves data modeling, optimization, and analytics to enhance global operations. Ideal candidates will have proven experience in data science for supply chain, strong skills in Python and SQL, and a passion for solving complex problems. This position offers the potential for permanent employment after a 12-month contract.

Formación

• Proven experience in data science for supply chain/logistics.
• Hands-on knowledge of mathematical optimization techniques.
• Strong background in Python, SQL, and modeling tools.

Responsabilidades

• Lead full lifecycle of supply chain network modeling.
• Conduct root cause analysis to understand deviations.
• Monitor KPIs and trends to detect performance drift.

Conocimientos

Data science for supply chain/logistics

Network modeling

Mathematical optimization techniques

Python

SQL

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:

• 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.
• 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.