Role overview
This role strengthens the core of our AI scheduling engine. You will build and optimise the models that power Connected Scheduling, improve our internal data science capability, and work closely with engineering to deliver fast, accurate, and reliable solving at scale.
Responsibilities
- Build, optimise, and maintain production-grade AI models for complex rota scheduling
- Improve data pipelines, workflows, and experimentation processes to enhance model reliability
- Collaborate with engineering to embed AI into core product workflows
- Apply scientific best practice to ensure accuracy, fairness, and compliance across all models
- Strong end-to-end data science skills with experience deploying models into production
- Deep expertise in Python, ML frameworks, optimisation methods, and cloud engineering
- A scientific, hypothesis-driven mindset with high attention to accuracy and rigour
- Ability to work with messy real-world data and design robust solutions
- Clear communicator who can work effectively with engineering and product teams
- A degree (Masters and/or PhD preferred but not required) in a numerical field such as mathematics, statistics, physics, computer science, engineering or another STEM-oriented subject
- Demonstrable experience in delivering production-grade code
- Some formal training in (or comparable deep practical exposure to) descriptive statistics, probability, inferential statistics, software development, and general data science fundamentals.
- The wider Python (3) data science stack and ecosystem (such as Pandas, NumPy, Jupyter notebooks, SciPy, FastAPI, Flask, Matplotlib, and similar)
- Core ML and DL frameworks (such as PyTorch (strongly preferred), Keras, TensorFlow, scikit-learn, and similar)
- Cloud compute, infrastructure, services, and deployment w.r.t. end-to-end data science (ideally AWS (such as S3, EC2, Lambda, ECR, ECS))
- Data visualisation methods and tools (such as Matplotlib, Bokeh or Seaborn)
- CI/CD
- Git
- An appreciation for solid coding practices
- Constraint/constrained optimisation and programming (particularly using metaheuristics for scheduling problems) in relation to both practical solvers and formal theory
- OptaPlanner/TimeFold or Google OR-Tools
- Basic containerisation via Docker
- MLOps platforms, services, and tools (such as DVC, MLflow, SageMaker or Weights & Biases)
- Agentic applications and/or conversational interfaces
- SQL and relational DBs (such as Postgres, Aurora or Athena)
- No-SQL DBs (such as MongoDB)
- Java
- Talent Screen: We’ll book you in for a quick introductory chat, and to answer any initial questions you might have.
- Meet your manager: We’ll book you in for a first interview with your potential future manager, so you can learn more about the role and we get a deeper understanding of your experience.
- Technical Interview - Pair Coding: We’ll have some fun working on a practical and relevant problem together. We’re particularly keen to understand how you approach writing code and the way you think about a problem. You’ll be provided with a brief the day before so will have a limited time to prepare.
- Values Interview: You’ll meet more members of the team to talk about the Lantum Values. This will be an opportunity for them to ask competency questions and also the chance for you to ask questions about life at Lantum.
Benefits
- ️ Health Cash Plan:
- Cash refunds for physio, dental, and other health related costs.
- An Employee Pricing Program that grants you access to special, non-public discounts to gyms and top retail brands.
- Plus access to a 24/7 counselling and support helpline.
- More than me: Our goals are too big to achieve on our own, it takes diverse skills and various people to achieve greatness.
- Care a lot: Doing the right thing isn’t optional. We care a lot about our users, the NHS and each other. We hold each other to the highest standards and earn our reputation every day.
- See it thru: We’re constantly looking for excellence. We take pride in planning and execution of all types of work, and we’re not deterred by bumps in the road or adversity. When we see obstacles, we relish the challenge and keep going.
- Think around corners: We always stay ahead of the curve. All of us share a responsibility to challenge the status quo, think outside the box, turn problems on their head and turn weaknesses into strengths.
- Bounce back & learn: Being brave, taking risks and trying new things. It’s better to take risks and learn from them and being open to changing from what you learned is what makes us successful.
Tags & focus areas
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