Lead Data Scientist And Machine Learning Lead

Lorien; Barcelona; Híbrido; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Lorien seeks a Lead Product Data Scientist to join a cross-functional product squad and shape decision-support software for complex operations. You will design, build and industrialise ML and optimisation solutions, collaborating with software engineers, product managers and business stakeholders.

Hybrid role, 6-month contract, with strong MBB consultancy experience desirable. You will drive production-ready analytics, analytics-driven decision making, and robust data pipelines in a fast-paced

Formación

• Strong expertise in machine learning, optimisation, operational research, or a related discipline.

Responsabilidades

• Understand business challenges and identify opportunities where data science and optimisation improve decision-making.
• Conduct analytical investigations and data visualisation to uncover insights and evaluate potential solutions.
• Develop and validate machine learning and optimisation models in Python.
• Build scalable, production-ready features using software engineering best practices.
• Create automated data processing and data quality pipelines.
• Integrate models into orchestration frameworks and cloud deployment environments.
• Implement testing, monitoring, and error-handling for reliability.
• Collaborate with stakeholders to gather requirements and demonstrate value.
• Contribute to product roadmap discussions and balance short-term delivery with long-term value.
• Collaborate in an Agile environment with code reviews and documentation.

Conocimientos

Machine learning

Optimization

Python

SQL

AWS

Git

Automated tests

Communication

Stakeholder management

Herramientas

MLflow

SageMaker

DVC

Airflow

Dagster

Gurobi

Descripción del empleo

Lead Product Data Scientist - MBB Consultancy experience highly desirable 6 month contact - hybrid

About the Role

We are looking for a talented Data Scientist to join a growing product team developing advanced decision-support software that helps optimise complex operational environments. Working as part of a cross-functional product squad, you will design, build and industrialise machine learning and optimisation solutions that drive real-world business outcomes. This is an exciting opportunity for someone who enjoys solving complex problems, building production-grade data science solutions and working closely with software engineers, product managers and business stakeholders.

What You'll Be Doing

As a Data Scientist, you will be involved throughout the product lifecycle, from identifying opportunities through to delivering robust, production-ready solutions.

Responsibilities

• Understanding business challenges and identifying opportunities where data science and optimisation can improve decision-making.
• Conducting analytical investigations and data visualisation to uncover insights and evaluate potential solutions.
• Developing and validating machine learning and optimisation models in Python.
• Building scalable, production-ready features using software engineering best practices.
• Creating automated and resilient data processing and data quality pipelines.
• Integrating models into orchestration frameworks and cloud-based deployment environments.
• Implementing testing, monitoring, logging and error-handling capabilities to ensure reliability.
• Working closely with stakeholders to gather requirements, demonstrate value and support product adoption.
• Contributing to product roadmap discussions and helping balance short-term delivery with long-term product value.
• Collaborating within an Agile development environment, including code reviews, documentation and continuous improvement activities.

Essential Skills & Experience

• Strong expertise in machine learning, optimisation, operational research, or a combination of these disciplines.
• Proficiency in Python and common data science libraries such as pandas, NumPy and scikit-learn.
• Experience applying analytical techniques to solve real-world business problems.
• Strong SQL and data engineering capabilities.
• Experience working with cloud platforms, ideally AWS.
• Familiarity with Git version control and software development best practices.
• Experience writing and maintaining automated tests.
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Strong problem-solving, prioritisation and stakeholder management skills.

Desirable Experience

• Exposure to optimisation tools such as Gurobi.
• Experience with ML lifecycle and MLOps tooling such as MLflow, SageMaker or DVC.
• Knowledge of workflow orchestration platforms such as Airflow or Dagster.
• Experience with CI/CD pipelines, containerisation and cloud-native deployments.
• Experience working on operational, transportation, logistics, network or optimisation-related challenges.
• Experience developing production-scale machine learning or optimisation products.

Please note that this role can also be based in the UK/Dublin with travel to Barcelona.