---
title: 'Data Scientist – Computational Genomics, 12-month FTC at relationrx'
canonical: 'https://feeny.ai/job/data-scientist-computational-genomics-12-month-ftc-relationrx-london-9d611jcw9kah'
type: 'job'
last_seen: '2026-10-16'
---

# Data Scientist – Computational Genomics, 12-month FTC at relationrx

- **Company:** relationrx
- **Location:** London, United Kingdom
- **Employment:** full-time
- **Posted:** 2026-10-05
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.ashbyhq.com/relationrx/23787cce-59d0-4990-89a7-d6a49990ece9

## Job description

## About Relation

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. We are committed to building diverse and inclusive teams. Relation is an 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. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

The opportunity This is a unique opportunity for a Data Scientist to bridge the gap between computational genomics and machine learning at scale. Operating at the genomics-ML interface, you will shape our computational genomics efforts to accelerate target identification and validation across diverse therapeutic areas, leveraging large-scale human genetics resources — genetic discovery, biobanks, OMICs, single-cell atlases and other internal datasets— to gain actionable insight. By building, refining and deploying cutting-edge ML-focussed methods you will inform robust functional prioritisation frameworks, mechanistic hypotheses, and strategic decision-making across the organisation.

Day to Day you will:

- Apply, build, refine and integrate statistical models to gain insight from genomics, transcriptomics and other OMICs datasets and support target discovery and validation.
- Work cross-functionally at the ML-genetics interface to identify opportunities, solve problems and implement solutions for shared insight
- Integrate human genetics evidence with OMICs datasets (e.g. transcriptomics, proteomics) to uncover disease mechanisms and prioritise actionable targets.
- Develop scalable computational workflows for reproducible analysis within Relation’s existing stack
- Partner closely with experimental and machine learning researchers to validate hypotheses, interpret results, and guide downstream studies.
- Communicate findings clearly to internal stakeholders, including presenting methods, results, and recommendations.
- Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility.

Professionally, you will have

- PhD in statistical genetics, genomics, computational biology, machine learning, bioinformatics, or a related quantitative field.
- Knowledge of machine learning techniques applied to biological data
- Experience in quantitative genomics, statistics, bioinformatics, or multi-omics data analysis.
- Proficiency in Python (preferred), or R, and familiarity with high-performance computing environments, collaborative coding and version control (e.g. git)
- Bonus experience:
- Familiarity with single-cell transcriptomics or patient-derived datasets.
- Experience working in interdisciplinary/matrixed teams within biotech or pharma settings.
- Understanding of the end-to-end drug discovery process and how genetic evidence informs decision-making.

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!

RECRUITMENT AGENCIES: Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.

Relation is a committed equal opportunities employer.

## About relationrx

## Company Overview
- **One-liner**: Relation Therapeutics is an end-to-end biotech company using single-cell multi-omics and machine learning to discover and develop transformational medicines for devastating diseases.
- **Entity Type**: Private (Seed/venture-backed; total funding $139M)
- **Headquarters**: London, United Kingdom (with offices in Miami Beach, US, and presence in Italy & India)
- **Founded**: 2019
- **Founders**: Charles Roberts, Benjamin Swerner, and Jake Taylor-King

## Core Business
- **Primary industry**: Biotechnology / Drug Discovery & Development
- **Target customers**: B2B – partnerships with large pharma (Novartis, GSK, Deerfield); ultimately patients for its own pipeline
- **Mission**: “Understand human biology in an unprecedented way; discovering therapies that will treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays and machine learning to drive disease understanding — from cause to cure.”

## Products & Services
- **Lab-in-the-Loop Platform**: An integrated technology stack combining single-cell analysis, genomics, and machine learning to identify druggable targets and develop transformational medicines.
- **Pipeline**: Preclinical/early-stage programs in osteoporosis (first indication announced March 2023) and atopic diseases (strategic collaboration with Novartis announced December 2025). Further undisclosed programs advanced via partnerships with GSK and Deerfield Management.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric**: Total funding of $139M (as of 2026); annual revenue estimated at $1.5M (LinkedIn estimate)
- **Notable Investors/Partners**:
  - DCVC, N Ventures (NVIDIA), Magnetic Ventures, Khosla Ventures, Firstminute Capital, Meltwind, Hitachi Ventures, ARK Invest
  - Strategic partners: Novartis (collaboration on atopic diseases), GSK ($15M equity investment and partnership), Deerfield Management (collaboration to form new companies from targets)
  - Grant from Bill & Melinda Gates Foundation (2020)
- **Growth Signals**:
  - Headcount grew 51.8% YoY to ~97 employees (LinkedIn)
  - Opened new labs in London (opened Feb 2023 by Nobel laureate Sir Paul Nurse)
  - Access to NVIDIA’s CAMBRIDGE-1 supercomputer
  - Multiple new funding rounds: $25M seed (June 2022), $35M seed-2 (March 2024), $15M from Novartis (Dec 2024), $26M further investment (2026)
  - Active job postings: 17 positions (as of mid-2026), with monthly postings up 54.5%

## Competitive Advantages
- **Differentiated platform**: Proprietary “Lab-in-the-Loop” approach that integrates wet-lab single-cell assays with machine learning, enabling high-resolution target discovery directly from patient tissue.
- **Top-tier compute**: Exclusive access to NVIDIA’s most powerful UK supercomputer and deep partnerships with NVIDIA, Mila, and academic leaders.
- **World-class talent**: Scientific advisory board includes Nobel laureate-level researchers and professors from MIT, Stanford, ETH Zurich, and Oxford; team drawn from GSK, BenevolentAI, Wellcome Sanger, and top universities.
- **Pharma validation**: Strong collaboration and equity investments from Novartis, GSK, and Deerfield signal confidence in the platform and pipeline.

## Strategic Focus
- **Priority areas**: Advancing internal pipeline in osteoporosis and atopic diseases; expanding collaborations with pharma to co-develop novel therapeutics; continuing to invest in AI/ML capabilities and single-cell technology.
- **Growth direction**: Scaling the team (especially in machine learning, data science, and biology), forming new spin-out companies with Deerfield, and deepening the use of generative AI for drug design.

## Why Work Here
- **Culture**: Emphasizes collaboration, empowerment, compassionate candor, and a winning attitude. “We set ambitious goals pushing boundaries with a high-performing mindset.”
- **Team**: Highly interdisciplinary – biologists, ML engineers, data scientists, computational chemists, and drug developers working together under one roof.
- **Location**: London HQ with hybrid possibility for some roles; research roles require on-site lab work (lab in King’s Cross area).
- **Perks**: Not publicly detailed, but the company offers the chance to work on cutting-edge AI + biology problems, access to NVIDIA supercomputing, and the impact of bringing new medicines to patients.
- **Engineering/Research Culture**: Strong focus on open collaboration with academia (e.g., Mila, Scripps, Gates Foundation); active hiring for senior ML scientists, computational biologists, and data engineers.

## Sources
1. [relationrx.com](https://www.relationrx.com/)
2. [relationrx.com/careers](https://www.relationrx.com/careers)
3. [relationrx.com/about](https://www.relationrx.com/about)
4. [LinkedIn – Relation Therapeutics](https://uk.linkedin.com/company/relation-therapeutics)
5. [jobs.ashbyhq.com/relationrx](https://jobs.ashbyhq.com/relationrx)

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