At a Glance
- Tasks: Analyse high-dimensional biological datasets to drive disease understanding and drug discovery.
- Company: Join Relation, a pioneering TechBio company transforming medicine with cutting-edge technology.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with diverse teams and excellent career advancement opportunities.
- Why this job: Make a real impact in healthcare by applying your data science skills to save lives.
- Qualifications: PhD in computational biology or related field, with strong experience in high-dimensional biological data.
The predicted salary is between 60000 - 80000 £ per year.
Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure.
We are seeking a Senior Data Scientist, Computational Biology to join Relation, working at the intersection of single-cell biology, spatial omics, and machine learning. In this role, you will apply advanced computational and statistical approaches to analyse high-dimensional biological datasets, generating insights that directly inform disease understanding and drug discovery. You will sit within the Single Cell & Spatial Omics function, working closely with ML researchers, experimental scientists, and software engineers to translate complex biological data into actionable knowledge. This is a highly collaborative, scientifically driven role, suited to someone who enjoys working deeply with data, challenging models with biological insight, and contributing meaningfully to interdisciplinary research programmes.
Day to day, you will:
- Analyse and interpret single-cell, spatial, and other multi-omics datasets to uncover biological mechanisms relevant to disease and therapeutic intervention.
- Develop and apply statistical and computational methods for transcriptomics and related omics data.
- Use domain expertise to design rigorous evaluation tasks that test, challenge, and refine ML models.
- Collaborate closely with ML scientists to inform model assumptions, features, and interpretation.
- Work with experimental teams to help design experiments and validate computational hypotheses.
- Clearly communicate insights, results, and methodologies to internal stakeholders and contribute to scientific publications.
Professionally, you will have:
- A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative field.
- Strong experience working with high-dimensional biological data, including transcriptomics and other omics modalities.
- Proficiency in Python, with experience in scientific computing and data analysis.
- A solid understanding of statistical modelling and quantitative methods applied to biological data.
- Experience with Bayesian models.
Bonus experience:
- Hands-on experience with single-cell and/or spatial omics data, including patient-derived samples.
- Familiarity with machine learning approaches used in biological or biomedical research.
- Experience working in interdisciplinary teams spanning biology, data science, and ML.
- Exposure to scalable computing environments.
Personally, you:
- Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
- Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
- Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
- Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
- Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.
Relation is a committed equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.
Senior Data Scientist - Computational Biology employer: Relation
Relation is an exceptional employer, offering a dynamic and collaborative work environment where innovation thrives at the intersection of technology and biology. Employees benefit from a culture that prioritises professional growth, with opportunities to engage in cutting-edge research and contribute to impactful projects aimed at transforming medicine. Located in a vibrant tech hub, Relation fosters a diverse and inclusive atmosphere, ensuring that every team member's insights are valued and that they can make meaningful contributions to the future of healthcare.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - Computational Biology
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to computational biology and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both scientists and data experts.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at Relation.
We think you need these skills to ace Senior Data Scientist - Computational Biology
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 work with high-dimensional biological data and any relevant machine learning projects to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about computational biology and how your background makes you a great fit for our team. Share specific examples of your work that demonstrate your expertise and enthusiasm.
Showcase Your Collaboration Skills:Since this role is highly collaborative, mention any experiences where you've worked with interdisciplinary teams. We love seeing how you’ve contributed to shared goals and tackled challenges together!
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 the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Relation
✨Know Your Data Inside Out
Before the interview, dive deep into the types of high-dimensional biological datasets you'll be working with. Brush up on your knowledge of transcriptomics and spatial omics, and be ready to discuss how you've applied statistical methods in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working closely with ML researchers and experimental scientists, prepare examples that highlight your experience in interdisciplinary teams. Think about specific instances where you contributed to a project by bridging the gap between data science and biology.
✨Prepare for Technical Questions
Expect to face technical questions related to Python, statistical modelling, and machine learning approaches. Practise explaining complex concepts in simple terms, as you'll need to communicate insights clearly to stakeholders who may not have a technical background.
✨Demonstrate Your Problem-Solving Mindset
Be ready to discuss how you've tackled challenges in previous roles, especially those involving data analysis and model evaluation. Highlight your ability to take ownership of your work and proactively seek solutions, as this aligns with the company's values.