Director of Data Science

Engitix
London
2 weeks ago
Create job alert

Your mission

We are seeking a Director of Data Science to lead a high-impact team driving data-driven insights and platform development. The Director will oversee two complementary efforts:

  • A portfolio delivery team focused on applying computational and bioinformatics approaches to internal and external discovery efforts
  • A platform development team responsible for building scalable infrastructure, computational tools, and ML/AI-driven capabilities to support ongoing and future research

Key Responsibilities:

Strategic Development

  • Provide strategic direction for data science initiatives, ensuring alignment with company research goals and priorities across all stages of drug discovery, from target ID and validation to translational studies
  • Work closely with internal and external discovery teams, bioplatforms, and external partners to support research and translational objectives, balance immediate project needs with long-term platform development, and optimize resource allocation and execution

Team & Organizational Management

  • Directly manage a small team delivering project-driven analyses across multiple therapeutic areas, and a Platforms lead responsible for delivering scalable, reusable computational tools and data infrastructure
  • Foster a collaborative, high-accountability culture that encourages scientific rigor, innovation, and cross-functional engagement
  • Drive recruitment, mentorship, and career development within the data science team
  • Champion best practices in reproducible research, data governance, and AI/ML model deployment

Technical Leadership & Innovation

  • Stay current on emerging AI/ML approaches, including structural biology (e.g., AlphaFold-style models), multimodal analytics (e.g., integration of omics, imaging, text), and digital pathology image analysis
  • Ensure that ML/AI innovations are effectively translated into research impact, working closely with experimental biologists and therapeutic area leads
  • Guide the application of bioinformatics and statistical methods to functional genomic screens (e.g., CRISPR, RNAi, perturbational assays), as well as scalable computational approaches to target and biomarker discovery and validation

Your profile

The ideal candidate has worked throughout drug discovery, from target identification and validation, to lead discovery and optimization, through to partnering with translational teams on preclinical and biomarker studies. They bring deep expertise in bioinformatic analysis of high-throughput functional genomic screens and proteomics, stay at the forefront of ML/AI innovations in structural biology, multimodal analytics, and/or imaging, and have a proven track record of leading and mentoring teams in biotech or pharmaceutical settings.

Required

  • Ph.D. (or equivalent experience) in Bioinformatics, Computational Biology, Machine Learning, or a related field
  • 10+ years of experience in computational biology, bioinformatics, or AI/ML with at least 5 years in biotech or pharma industry
  • Broad technical fluency across omics, imaging, AI/ML, and statistical modeling approaches
  • Expertise in analyzing high-throughput functional genomic screens (e.g., CRISPR, RNAi, Perturb-seq)
  • Strong knowledge of AI/ML applications in structural biology, multimodal data integration, and/or imaging
  • Demonstrated experience building and leading high-performing data science teams, including direct people management and developing other leaders
  • Ability to balance competing priorities across platform development and project execution

Preferred

  • Experience working in drug discovery, target identification, or precision medicine
  • Track record of successful collaboration with wet-lab scientists and research leadership
  • Familiarity with cloud-based computational infrastructure (AWS, GCP) and scalable bioinformatics workflows

Why us?

  • Be part of a motivated, dynamic team supporting cutting edge drug discovery
  • Constant opportunities to learn, grow, and explore the many opportunities for data science to have impact on drug discovery and development
  • State of the art offices at The Westworks, White City London
  • Competitive reward package including private medical insurance, bonus, pension, and much more!

About us

Engitix is a growing biotech company based in White City Place, West London. We are dedicated to developing better therapies for advanced fibrosis and solid tumours by leveraging our pioneering extracellular matrix (ECM) platform. Our platform allows the synthesis of realistic in vitro 3D models that serve as tools to transform our ability to identify new targets and biomarkers, determine mechanisms of action and more accurately predict the efficacy of therapeutic candidates. 

Join us today in our mission to create a healthier future for patients with life-threatening diseases such as fibrosis and cancer.

Related Jobs

View all jobs

Director of Data Science

Data-Driven Forecasting Analyst – (Pharmaceutical Consultancy)

Principal Data Scientist - NLP

Data Science Director

Director of Growth Engineering (Based in Dubai)

Senior Manager Marketing Data & Insights Strategy

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.