Lead Data Scientist

Lorien; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Lorien is seeking a Lead Data Scientist to join a growing product team building decision-support software that optimises complex operational environments. You will design, build and industrialise ML and optimisation solutions, collaborating with software engineers, product managers and business stakeholders.

In this role you will lead production-grade data science, guide the product lifecycle from opportunities to deployed solutions, and contribute to roadmap discussions while balancing

Qualifications

• Strong expertise in machine learning and optimisation and/or operational research.
• Proficiency in Python with data science libraries (pandas, NumPy, scikit-learn).
• Experience with cloud platforms (ideally AWS) and ML lifecycle tooling (MLflow, SageMaker or DVC).
• Hands-on data engineering and building production-grade data pipelines.

Responsibilities

• Identify opportunities where data science and optimisation can improve decision-making across operations.
• Develop, validate and productionise ML and optimisation models in Python.
• Build scalable, production-ready features following software engineering best practices.
• Create resilient data processing pipelines with testing, monitoring and logging.
• Collaborate with software engineers, product managers and stakeholders, gathering requirements and demonstrating value.
• Contribute to product roadmaps and balance short-term delivery with long-term value.
• Work in an Agile environment with code reviews, documentation and ongoing improvements.
• Experience with workflow orchestration platforms like Airflow or Dagster and cloud deployments.

Skills

Python

SQL

ML & Optimization

MLOps

Cloud AWS

Gurobi

Airflow

Dagster

ML lifecycle

SageMaker

MLflow

DVC

Git

Tools

Pandas

NumPy

scikit-learn

TensorFlow/PyTorch

Docker

Job description

Lead Data Scientist - MBB Consultancy experience highly desirable

12 month contact

London/Dublin - hybrid

Please note that this role will also require travel to Barcelona.

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 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.
• 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.
• 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.