Data Scientist

JR Spain; Valladolid; Presencial; EUR 40.000 - 60.000; A tiempo parcial

Descripción de la vacante

Una empresa busca un Data Scientist especializado en Supply Chain Optimization para un contrato de 12 meses. El candidato ideal tendrá experiencia en modelado y optimización en el ámbito de la logística, dominando herramientas como Coupa y Llamasoft. Se ofrece una oportunidad de trabajo remoto con un potencial de conversión a un rol permanente, ideal para quienes buscan aportar soluciones inteligentes y optimizar operaciones globales.

Formación

• Experiencia comprobada en ciencia de datos para supply chain/logística, especialmente en modelado y optimización.
• Conocimientos prácticos de técnicas de optimización matemática (MILP) y diseño heurístico.
• Fondo sólido en Python, SQL y herramientas de modelado.

Responsabilidades

• Dirigir el ciclo de vida completo del modelado de la red de la cadena de suministro.
• Normalizar y limpiar datos históricos de la cadena de suministro.
• Identificar cuellos de botella en toda la cadena de suministro.

Conocimientos

Data Science

Optimización

Modelado

Python

SQL

MILP

Herramientas

Coupa

Llamasoft

Azure Cloud

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.