Job Specifications
Who We Are
Our mission is to transform how healthcare organisations work together with their workforce. Our Connected Scheduling™ platform connects healthcare organisations and their staff giving them more autonomy and control on how and when they work. Over 50% of UK GP practices use Lantum, and over 30% of UK hospitals rely on Lantum workforce products. We have developed a completely new approach to scheduling staff using AI to balance the vast amounts of complexities in workforce scheduling and we have seen game-changing results. We have not only saved millions for the NHS, but we have countless stories of how we have improved the lives of clinicians who, for the first time, are able to plan their work lives around their personal lives.
What sets us apart is not only our leading edge technology and approach to innovation, it's our culture and our strength of mission. Our incredible team is the driving force behind our success and this propels our competitive edge. We are diverse (10+ nationalities and 53% female workforce), we are authentic and true to ourselves, we are creative and focused and we work hard together to change our industry. Our team is supported to deliver their best work with clear career progression and a strong feedback culture.
We have a bright and modern office which you can work from throughout the week and 3 core office days per week (Monday, Tuesday & Wednesday) where the whole team comes together.
About The Role
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
Requirements
About You - We'll be looking for
General
Our ideal candidate is an individual who has:
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
Education and Training
Our ideal candidate is an individual who has:
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
Technical Experience
An ideal candidate has demonstrable skills and experience in the following technologies.
Required (ideally most of the following):
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
Prior exposure to or interest in some of the following is highly beneficial:
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
Interview process
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 mee
About the Company
Lantum is a workforce management platform that makes it easier for healthcare providers to mobilise their workforce, and for clinicians to work more flexibly. Our Connected Scheduling platform gives you a staff bank, rota tool and a clinician network all in one place to improve fill rates, cut admin time, and reduce costs. We started life as Network Locum in 2012. While working as part of the NHS London Transformation team, Lantum CEO Melissa Morris saw firsthand how inefficiencies in staffing were drastically affecting the ...
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