About Us:

At Sensyne Health we have created a unique partnership with NHS partner Trusts and US Healthcare Providers that unlocks the value of clinical data for research while safeguarding patient privacy. We use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, de-identified patient data to solve serious unmet medical needs across a wide range of therapeutic areas. This enables a new approach to clinical trial design, drug discovery, development and post-marketing surveillance. Alongside this partnership, we develop clinically validated software applications that create clinician and patient benefit, while providing highly curated data.

The Team:

Our Data and Machine Learning Engineering team is currently expanding to bring further expertise into a multidisciplinary environment. The aim is to drive the next generation of innovation for better patient outcomes, whilst harnessing some of the industry’s most progressive AI approaches. This is centred on data-efficient machine learning (ML) algorithms. Working to an agile methodology, the nature of our team is collaborative with an emphasis on genuine passion for healthcare. The roles are research and development based with high potential for professional growth, support towards our business goal and ongoing contribution to the development of healthcare.

Responsibilities:

• Create and build optimal data pipelines for data analytics products, ensuring data flow is scalable, robust and performant
• Build vital tools and infrastructure to monitor and understand the data flow outputs and performance
• Work closely with data scientists, ML engineers and enterprise infrastructure teams to speed up delivery of cloud data services
• Work with ML researchers to build feature databases, as well as standardised & traceable datasets from which models are created

• Optimise the data analytics delivery process by implementing data provisioning automation, data pipeline testing and data quality monitoring
• Collaborate/lead other ETL/Data Engineers

Essential:

• University degree in computer science or comparable qualification
• At least two years of experience in building ETL and/or data pipelines (ingest & store, data preparation & transformation, automated quality testing)
• Substantial experience with cloud infrastructure and provisioning resources for data (our stack is Azure Data Factory/Synapse / ML Studio based)
• Strong programming background, with:

• Advanced to expert knowledge of relational and non-relational databases (e.g. PostgreSQL, Transact-SQL, Cosmos/MongoDB, Cassandra, etc.)
• Extensive experience in Python (common libraries we use are pandas, numpy, dask, pytest, dbt, sqlalchemy, sklearn, etc.)
• Solid understanding of data structures and data pipeline architecture, including the operational trade-offs of various designs

• Ability to maintain a test suite and write clear maintainable code using e.g. CircleCI, GitlabCI, Github Actions.
• Knowledge in maintaining application code via source control version tools such as Git and GitHub
• Experience as a developer in an agile software development team

Desirable:

• Previous experience working closely with Data Scientists and/or ML researchers on analytics and ML pipelines is valuable.
• Previous experience and familiarity with healthcare data
• Solid understanding of modern ML approaches and ML pipeline architecture, including the operational trade-offs of various designs, and knowledge in ML frameworks, i.e. TensorFlow and Pytorch.
• Knowledge of Apache Spark, particularly PySpark
• Solid understanding of the UNIX operating system and its concepts

Personal Qualities:

• Communication: You are able to discuss technical issues at all levels of the business and provide clear presentations of technical work.
• Technical: You will be a data geek! One who enjoys seeing value and insight derived from data; you will be a technology and cloud enthusiast, who embraces new ideas and processes, yet keeps a keen eye on delivery and providing value.

• Company share option scheme
• 5% employer matched salary sacrifice Pension scheme
• Life Assurance & Income protection
• A range of health, wealth and lifestyle benefit plans including BUPA, Gym and holiday trade options
• Electric Vehicles & Cycle to work schemes
• Proactive career development