At a Glance
- Tasks: Analyse complex biological datasets and apply machine learning to drug discovery challenges.
- Company: Innovative TechBio company at the forefront of computational biology and drug discovery.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with opportunities to work on groundbreaking projects.
- Why this job: Make a real impact in therapeutic discovery using cutting-edge technology and data science.
- Qualifications: Strong background in Data Science, Computational Biology, and experience with ML in biological contexts.
The predicted salary is between 60000 - 80000 £ per year.
We're partnering with an innovative TechBio company at the intersection of computational biology, machine learning, and drug discovery. The team is building advanced computational approaches to better understand human biology and accelerate therapeutic discovery across complex diseases.
This role is ideal for a scientifically grounded data scientist with a strong computational background who thrives on interpreting machine learning outputs in a biological context — not just building models, but extracting meaningful biological insight that can influence discovery decisions.
What You'll Be Doing
- Analyse complex biological and multi-omics datasets
- Apply ML and statistical modelling to drug discovery challenges
- Interpret model outputs in a biological context
- Work with pathway databases, knowledge graphs, and large-scale biological data
- Collaborate with computational biology and data science teams
What We're Looking For
- Strong background in Data Science, Computational Biology, Bioinformatics, Statistics, Computer Science, Physics, Mathematics, or related fields
- Experience in biotech, pharma, drug discovery, or TechBio
- Strong Python and/or R skills
- Experience with ML applied to biological data
- Familiarity with genomics, single-cell, spatial, proteomics, or multi-omics data
- Experience with Reactome, KEGG, OpenTargets, STRING, or similar databases is a plus
- Strong critical thinking and ability to interpret ML outputs biologically
Preferred Background
- Production or implementation experience
- Multi-modal / cross-modality biology experience
- Exposure to LLMs or AI agents
If you're excited by the opportunity to combine machine learning, computational biology, and translational science to drive real-world therapeutic discovery, we'd love to hear from you. Apply directly or reach out for a confidential discussion.
Senior Data Scientist – Computational Biology & Drug Discovery in London employer: Hlx Life Sciences
Join a pioneering TechBio company in London that is at the forefront of computational biology and drug discovery. With a strong emphasis on innovation, our collaborative work culture fosters continuous learning and growth, offering employees the chance to engage with cutting-edge technologies and make impactful contributions to therapeutic advancements. Enjoy a hybrid working model that promotes work-life balance while being part of a team dedicated to transforming human health through data-driven insights.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist – Computational Biology & Drug Discovery in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biology and drug discovery. Attend meetups, webinars, or conferences where you can connect with potential employers and showcase your passion for the industry.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects related to machine learning and biological data analysis. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and R skills. Be ready to discuss how you've applied ML to biological datasets and be prepared to solve problems on the spot.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our innovative team.
We think you need these skills to ace Senior Data Scientist – Computational Biology & Drug Discovery in London
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 background in computational biology, machine learning, and any relevant projects that showcase your ability to interpret biological data.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about drug discovery and how your unique skills can contribute to our mission. Be specific about your experience with multi-omics datasets and any relevant tools you've used.
Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python or R, and any experience you have with ML applications in biological contexts. We want to see how you’ve applied these skills in real-world scenarios, so include examples!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Hlx Life Sciences
✨Know Your Data Inside Out
Make sure you’re well-versed in the specific biological and multi-omics datasets relevant to the role. Brush up on how these datasets are used in drug discovery and be ready to discuss your previous experiences with similar data.
✨Showcase Your ML Skills
Prepare to talk about your experience with machine learning, especially in a biological context. Be ready to explain how you've applied ML techniques to solve real-world problems in biotech or pharma, and don’t forget to highlight any specific tools or libraries you’ve used.
✨Interpretation is Key
This role requires not just building models but also interpreting their outputs biologically. Think of examples where you’ve successfully translated complex model results into actionable insights and be prepared to discuss them in detail.
✨Collaborative Spirit
Since collaboration is crucial in this role, think of instances where you’ve worked effectively with cross-functional teams. Be ready to share how you’ve communicated complex data science concepts to non-experts and contributed to team projects.
