Albus Health is a medical technology startup that develops intelligent remote monitoring systems. We are looking for a Data Science Lead to join us in our mission to improve lives of a billion people worldwide struggling with chronic respiratory conditions such as asthma and COPD.

Our potent combination of technical, clinical and commercial experts has allowed us to gain significant commercial traction in a relatively short duration. Our solution is now in use by some of the world’s largest pharma companies and we are preparing to scale up our operations domestically and overseas.

Albus have partnerships with top hospitals in the UK and some of Europe’s best clinicians. We have been running multiple carefully selected clinical studies and trials for several years, and as a result, acquired a wealth of data. This data will be instrumental to further advance our technology and to continue extracting valuable insights that would prevent emergencies and deaths for people struggling with chronic conditions.

Albus spun out from the Department of Engineering and Respiratory Medicine at Oxford University back in 2017 and have since then won multiple wards (including AI in Health and Care Award by UK’s Health Secretary and UK Research and Innovation). Albus is firmly backed with multi million pounds investment and we are now looking to expand our technical team in Oxford to develop new products and solutions that can operate at a global scale.


About the role

The data science lead position will largely be an R&D hands on role, adequately supported by other senior and more junior colleagues. The role will require researching, architecting and designing solutions that can then be taken forward by the lead and/or other data scientists in the team.

As part of the technology team, this role will be reporting directly to the CTO and will also have access to a range of clinical and industry experts to jointly steer research and identify the best solution to our customer’s problems. Our technology team is structured in efficient and compact teams or “squads” which helps us to keep management overheads low. The data science lead will be responsible for the Data Science team, with support from the CTO and other areas (Cloud, Firmware and QA).

One of the most important areas of ownership will be the sensory data captured (Acoustic and others). Given the volume of data and processing involved, software needs to be architected for efficiency and scale. You will be one of the key architects and developers behind a data analysis infrastructure that will process data from tens of thousands of patients in multiple countries, with a team of doctors, engineers and commercial experts. We are in a unique position because we have full control over the entire data pipeline benefiting from “cloud” and “edge” processing for us to use as required.


Core Responsibilities

  • Design suitable signal processing algorithms to address requirements, applying suitable AI/ML technologies and models as required.

  • Implement the data processing models, test results and validate outcomes.

  • Engage with our clinical and commercial teams to understand deeply the problems we need to solve.

  • Develop an intimate knowledge about the data available to us, including opportunities and challenges.

  • Contribute to further improve and automate our data collection pipelines, including data sources research, data collection, data cleaning, data labelling, etc.

  • Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems.

  • Sift and analyse data from multiple angles, looking for trends that highlight opportunities

  • Formulate hypothesis for model improvement/optimisation, test/validate hypothesis and optimise input data and chosen model

  • Grow, develop and lead the data science team and capability.


  • MSc or PhD in electrical engineering, information engineering, biomedical engineering, physics or related fields.

  • 5+ years experience working with digital signal processing, preferably in acoustic, wireless sensors or digital biomarkers.

  • Experience with frequency content and spectrum analysis and solid understanding of the different sources of noise, signal degradation and techniques to extract meaning from raw noisy signals.

  • 5+ years experience working with machine learning applied to signal processing and time series analysis, including implementation, training, tuning and evaluation of models.

  • Previous experience with classical ML models such as SVM, random forest, XGB boost as well as Deep Learning models.

  • Experience creating deep learning models using at least one of the following frameworks: TensorFlow, PyTorch, Keras.

  • High proficiency in Python programming


Desirable requirements

  • Practical know how on using cloud computing (AWS, Azure or GCP) to store and process data at scale as well as data management systems (e.g. MySQL or Data Marts or Data Warehouse)

  • Strong programming and computing skills (proficiency working with Linux OS’, Docker or Kubernetes, etc.)

  • Experience with other programming languages such as Matlab and/or C++ would be a bonus.

  • Experience working with a healthcare or medical technology startup will be a distinct advantage, specially with remote symptom monitoring products.

  • Demonstrable experience of managing independent projects, writing production code and growing a team.

  • Productisation experience for solutions with a significant machine learning, signal processing and electrical engineering components, encompassing cloud and hardware sub-systems. In particular in a regulated industry such as healthcare.


  • Competitive salary (based on experience)

  • Employer pension plan contribution

  • 30 days paid holidays.

  • Participation in share option scheme

  • Possibility of flexible working hours and remote working arrangements