Lead Product Data Scientist

Lead Product Data Scientist - MBB Consultancy experience highly desirableA continuación, encontrará un desglose completo de todo lo que se requiere de los posibles candidatos, así como la forma de presentar su candidatura.¡Mucha suerte!6 month contact - hybridAbout the RoleWe 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 DoingAs 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 & ExperienceStrong 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 ExperienceExposure 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.xqysrnhPlease note that this role can also be based in the UK/Dublin with travel to Barcelona.

6 month contact - hybridAbout the RoleWe 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 DoingAs 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 & ExperienceStrong 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 ExperienceExposure 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. xqysrnhPlease note that this role can also be based in the UK/Dublin with travel to Barcelona.