At a Glance
- Tasks: Analyse clinical data to drive insights and improve biosensing technology.
- Company: Sava is revolutionising health interaction with advanced biosensing technology.
- Benefits: High-ownership role, steep learning curve, and impactful work in a dynamic environment.
- Why this job: Join a mission-driven team making real changes in healthcare technology.
- Qualifications: MS in Data Science or related field, 4+ years experience with complex datasets.
- Other info: Collaborative culture focused on integrity and urgency.
The predicted salary is between 36000 - 60000 £ per year.
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.
Senior Data Scientist (Clinical Data Analytics) employer: Story Terrace Inc.
Contact Detail:
Story Terrace Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Clinical Data Analytics)
✨Tip Number 1
Network like a pro! Reach out to current employees at Sava on LinkedIn or other platforms. Ask them about their experiences and any tips they might have for the interview process. Personal connections can give you an edge!
✨Tip Number 2
Prepare for those technical interviews! Brush up on your data analysis skills, especially with time-series data. Be ready to discuss your past projects and how you've tackled complex datasets. Show us your problem-solving prowess!
✨Tip Number 3
Don’t forget to showcase your communication skills! We want to see how you can translate complex findings into insights that everyone can understand. Practice explaining your analyses in simple terms—this is key for cross-functional roles.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows your genuine interest in joining our mission-driven team at Sava. Let’s make it happen!
We think you need these skills to ace Senior Data Scientist (Clinical Data Analytics)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Data Scientist role. Highlight your experience with clinical data, time-series analysis, and any relevant projects that showcase your analytical prowess.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about the role and how your background fits with our mission at Sava. Share specific examples of your work with complex datasets and how you've communicated insights to diverse teams.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python, SQL, and any data visualisation tools you’ve used. We want to see how you’ve applied these skills in real-world scenarios, especially in R&D environments.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Sava!
How to prepare for a job interview at Story Terrace Inc.
✨Know Your Data Inside Out
Before the interview, dive deep into your past experiences with clinical data analysis. Be ready to discuss specific projects where you transformed complex datasets into actionable insights. Highlight your familiarity with time-series data and any challenges you faced, as this will show your problem-solving skills.
✨Brush Up on Statistical Techniques
Make sure you're well-versed in the statistical methods relevant to the role. Be prepared to explain how you've applied these techniques in real-world scenarios, especially in relation to sensor performance and data quality issues. This will demonstrate your analytical prowess and understanding of the limitations of different approaches.
✨Communicate Clearly and Confidently
Practice explaining your analytical findings in a way that’s accessible to both technical and non-technical stakeholders. Use examples from your previous work to illustrate how you’ve effectively communicated complex data insights. This is crucial for a cross-functional role like this one.
✨Show Your Passion for Biomedical Data
Express your genuine interest in biomedical and physiological data during the interview. Share what motivates you about working with sensor behaviour and how you stay updated on industry trends. This enthusiasm can set you apart and align you with the company’s mission.