Senior Data Scientist (Clinical Data Analytics)

Story Terrace Inc.; Greater London; On-site; GBP 60,000 - 85,000; Full time

Job summary

A leading health technology company in Greater London is seeking a Senior Data Scientist. This role involves analyzing clinical data from in-vivo studies, transforming complex time-series data into actionable insights, and collaborating with cross-functional teams. The ideal candidate should have a master's degree in a quantitative field, at least four years of relevant industry experience, and proficiency in Python and SQL. Strong communication skills and a proactive mindset are essential for success in this dynamic environment.

Qualifications

• At least 4 years of industry experience working with complex datasets in an R&D environment.
• Comfortable owning analyses end-to-end and translating findings.
• Strong interest in biomedical data and sensor behavior.

Responsibilities

• Analyse and manipulate clinical time-series data from in-vivo studies.
• Build, maintain, and improve reproducible analysis pipelines.
• Investigate data quality issues and communicate findings.

Skills

Data analysis

Statistical analysis

Python programming

SQL proficiency

Signal processing

Data visualization

Cross-functional collaboration

Education

MS in Data Science, Biomedical Engineering, Statistics or related field

Tools

Power BI

Git

Job description

About Sava

All the health information we need is within us. Just below the skin. SAVA is redefining the way people interact with their health by developing the most advanced biosensing technology science has to offer, capable of accessing bodily information in a painless, real-time and affordable way.

The Role

We are hiring a Senior Data Scientist (Clinical Data Analytics) to play a central role in the analysis and interpretation of clinical data collected from in-vivo testing of our device. You will be responsible for transforming time-series clinical datasets into actionable insights that inform device performance evaluation and broader company decisions.

The role is highly cross-functional. You will work closely with the clinical team to support trial design and data review and with R&D teams to provide data-driven input on device behavior, performance, and potential failure modes observed in real-world use. A key part of the role is not only quantifying performance, but also identifying and characterising issues or limitations in the data and clearly communicating them.

As our clinical programs expand, the volume and complexity of collected data will continue to grow. This role is therefore critical in ensuring that performance trends and uncertainties are rigorously assessed and communicated at both a technical and high-level summary view. The ideal candidate is comfortable owning analyses end-to-end and can effectively translate detailed statistical findings into insights that are accessible to a broad set of stakeholders across the organisation.

What You'll Do

• Analyse and manipulate clinical time-series data from in-vivo studies to evaluate sensor behavior, and use additional data sources to perform root-cause analysis when issues are observed.
• Build, maintain, and improve reproducible analysis pipelines to support scalable processing of clinical data.
• Investigate data quality issues, performance variability, and potential sensor limitations, and clearly communicate findings to clinical, R&D, and cross-functional teams.
• Act as a central analytical reference for clinical sensor performance, ensuring that results are interpreted consistently and rigorously across studies.
• Help establish and evolve methodologies and best practices for clinical data analysis as the company's clinical programs expand.
• Support long-term product and research decisions by translating complex clinical data into high-level performance trends and risks.

What We're Looking For

• Degree (MS) in Data Science, Biomedical Engineering, Statistics, or a related quantitative field.
• At least 4 years of industry experience working with complex datasets, in an R&D environment.
• Strong ability to analyse and interpret complex clinical and sensor data, with a focus on time-series data.
• Solid grounding in statistical analysis and modeling, including understanding assumptions and limitations of different approaches.
• Strong understanding of signal processing fundamentals
• Proficiency in Python for data analysis, including writing clear and maintainable code for time-series processing and statistical analysis
• Experience querying and working with relational and non-relational databases to support analysis and reporting
• Strong knowledge of SQL for data querying, manipulation, and aggregation across large datasets
• Familiarity with version control systems (e.g., Git) and collaborative development workflows.
• Experience using data visualisation tools (e.g., Power BI or similar) to communicate insights and performance trends effectively.
• Strong interest in biomedical and physiological data, with the motivation to understand sensor behavior and underlying mechanisms.
• Comfortable working in a cross-functional and fast-paced environment, collaborating with clinical, R&D, and other teams.
• Ability to clearly communicate analytical results, limitations, and trade-offs to both technical and non-technical stakeholders.
• Proactive mindset, with a sense of ownership over analyses and outcomes

Bonus Points For

• Experience in biotech companies
• Previous experience with CGM sensor data or physiological signals
• Experience in a start-up or scale-up environment

Why Sava?

This is a high-ownership, high-responsibility role in a company that’s building something complex, meaningful, and fast. The expectations are high, the learning curve is steep, and the work is often messy - but the impact is real.

We don't have room for egos or passengers. What we do have is a team of thoughtful, driven, and mission-aligned people who are committed to building something better—and doing it with urgency and integrity.