Data Scientists

As a key member of a product squad and reporting to the Lead Product Data Scientist, a Data Scientist will develop data pipelines, machine learning models, and complex optimisation models in the ODS software product suite. The Data Scientist is in charge of modelling and robust implementation of features contributing to an operations decision-support product. In developing a product’s core algorithm, the full-stack Data Scientist role will ensure that their features integrate seamlessly into the product’s technical stack (data ingestion, user interface, orchestration) as well as the business process and use case (e.g., to maximise impact and value realisation).

Required skills

Recent, hands-on commercial experience with Operational Research and optimisation

Strong experience with optimisation techniques (linear, non-linear, mixed-integer programming, constraint satisfaction, scheduling)

Proficiency in Python and optimisation/data libraries (e.g. SciPy, OR-Tools, Gurobi, CPLEX, Pandas, NumPy)

Solid data engineering skills (SQL, data pipelines, data quality)

Experience productionising models using cloud platforms (AWS preferred), experiment tracking, workflow orchestration, and CI/CD

Background in operations-heavy industries preferred (aviation, logistics, supply chain, retail)

Strong commercial mindset focused on solving real business problems

Excellent communication skills with the ability to engage confidently with non-technical stakeholders

Comfortable working independently in fast-paced, stakeholder-facing environments

Key responsibilities & duties include:

Design, build, and deploy data science and optimisation models across operational domains such as workforce planning and supply chain

Own use cases end-to-end: problem definition, modelling, experimentation, and production delivery

Work across multiple concurrent data science/optimisation streams within a small, agile team

Prototype and industrialise machine learning and optimisation models in Python, following software engineering best practices

Build and maintain robust data pipelines, testing, logging, and CI/CD for production-grade solutions

Diagnose performance, identify trade-offs, and optimise models for real-world operational constraints

Engage directly with business stakeholders to translate operational challenges into analytical solutions

Clearly communicate technical findings and recommendations to non-technical audiences

Contribute to feature prioritisation and roadmap discussions, balancing speed vs long-term value

The Data Scientist is also accountable for ways of working fit for an Agile cross-functional development squad, including:

Using Git-versioning best practices for version control

Contributing and reviewing pull-requests and product / technical documentation

Giving input on prioritization, team process improvements, optimizing technology choices

Working independently and giving predictability on delivery timelines

Desirable skills

Systems thinking

Detail oriented while understanding the big picture

Curious, self-motivated, proactive, and action-oriented

Creative and innovative

Resilient and flexible in light of changing priorities and approached

Data-driven

Pragmatic

Collaborative

A true believer in the power of using data to drive better decision making

A technologist, interested in keeping up with the latest and greatest in software development, optimization, and machine learning

Commitment to delivering business value