Lead Product Data Scientist

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 Youll 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 include: * 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.

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.