Senior Data Scientist - Single Cell & Spatial

Senior Data Scientist - Single Cell & Spatial

Full-Time 60000 - 80000 € / year (est.) No home office possible
Relation

At a Glance

  • Tasks: Drive transformative insights in drug discovery through advanced data analysis and collaboration.
  • Company: Join a pioneering TechBio company at the forefront of medicine innovation.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic, collaborative environment with a focus on interdisciplinary teamwork.
  • Why this job: Make a real impact on healthcare by solving complex biological problems.
  • Qualifications: PhD in computational biology or related field, with experience in multi-omics data analysis.

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 scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state‑of‑the‑art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact.

This is a unique opportunity for a senior data scientist to work on multi-omics and perturbational data to drive transformative insights into drug discovery. As a member of the Single Cell and Spatial Omics team, and embedded within one of the ML research teams, you will contribute advanced data analysis and domain expertise to challenge ML models that aim to predict and explain cellular decision‑making in disease.

Day to day, you will:

  • Develop and implement computational workflows for integrating and analysing multi-omics data.
  • Design statistical models for analysing transcriptomics and other omics datasets.
  • Use domain and data insights to design meaningful and challenging evaluation tasks for ML models.
  • Collaborate closely with ML modellers to develop model architectures.
  • Work with experimental teams to design and validate computational hypotheses.
  • Present findings and methodologies to internal stakeholders and contribute to publications.

Professionally, you will have:

  • A PhD in computational biology, bioinformatics, or a related quantitative field.
  • Extensive experience in multi-omics data analysis, including transcriptomics.
  • Proficiency in Python and familiarity with high‑performance computing environments.

Bonus Experience:

  • Familiarity with single-cell transcriptomics or patient‑derived datasets.
  • Knowledge of ML techniques applied to biological data.
  • A background in statistical modelling and algorithm development.
  • Experience working in interdisciplinary teams.

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.

Working style & culture at Relation:

At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting!

Relation is a committed equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender re‑assignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.

Senior Data Scientist - Single Cell & Spatial employer: Relation

Relation is an exceptional employer that fosters a collaborative and innovative work culture, where interdisciplinary teams unite to tackle complex challenges in drug discovery. Located in the heart of London, our state-of-the-art labs provide an inspiring environment for professional growth, offering opportunities to engage with cutting-edge technology and contribute to transformative medical advancements. We prioritise employee development and inclusivity, ensuring that every team member can thrive while making a meaningful impact on patient lives.

Relation

Contact Detail:

Relation Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Scientist - Single Cell & Spatial

Network Like a Pro

Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars. The more you engage with others, the better your chances of landing that dream job at Relation.

Show Off Your Skills

Don’t just talk about your experience; showcase it! Create a portfolio or GitHub repository with your projects related to multi-omics and machine learning. This will give potential employers a taste of what you can bring to the table.

Tailor Your Approach

When reaching out to potential employers, make sure to tailor your message to highlight how your skills align with their needs. Mention specific projects or experiences that relate to the role at Relation to grab their attention.

Apply Through Our Website

We encourage you to apply directly 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 being part of our team at Relation.

We think you need these skills to ace Senior Data Scientist - Single Cell & Spatial

Multi-Omics Data Analysis
Transcriptomics
Computational Workflows Development
Statistical Modelling
Machine Learning Techniques
Python Programming
High-Performance Computing

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 expertise in multi-omics data analysis and any relevant projects you've worked on. We want to see how you can contribute to our mission!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background fits with our goals at Relation. Be sure to mention any experience with interdisciplinary teams, as collaboration is key for us.

Showcase Your Technical Skills:Don’t forget to highlight your proficiency in Python and any experience with high-performance computing environments. We’re looking for someone who can hit the ground running, so make those skills stand out in your application!

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 you’re keen on joining our team at Relation!

How to prepare for a job interview at Relation

Know Your Multi-Omics Inside Out

Make sure you brush up on your knowledge of multi-omics data analysis, especially transcriptomics. Be ready to discuss specific projects where you've applied these techniques and how they relate to drug discovery. This will show that you understand the core of what Relation is all about.

Show Off Your Python Skills

Since proficiency in Python is a must-have, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot or discuss your previous work involving high-performance computing. Have examples ready that highlight your experience with computational workflows.

Collaboration is Key

Given the interdisciplinary nature of the role, be prepared to talk about your experience working in teams. Share examples of how you've collaborated with ML modellers or experimental teams, and how you’ve contributed to shared goals. This will show that you can thrive in a matrixed environment.

Communicate Clearly and Confidently

Practice articulating your findings and methodologies clearly, as you'll need to present to internal stakeholders. Think about how you can convey complex ideas simply and effectively. Good communication skills are essential for building strong working relationships and contributing to the team’s success.