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Head of Data Science

biomodal
London
1 week ago
Applications closed

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About Biomodal

Join the multiomic revolution! Over the last 20 years, genomic technologies have enabled significant discoveries that bring the promise of personalised medicine closer than ever before. But after two decades of research, it's clear that genetic variation only tells part of the story – biology is dynamic and more complex than A, C, T, G. Already, the added information from a multiomic view of biology is yielding important insights into cancer, ageing, and neurological disease, and is poised to revolutionise how we understand health and disease beyond canonical variation in DNA.


biomodal is an omics-based life sciences technology and analytics company, delivering products that bring the dynamism of our ever-changing biology into focus. Our team is dedicated to developing the most advanced solutions to interrogate and understand the complex interplay of genomics and epigenomics.


We have launched our first products, the duet +modC and duet evoC solutions, with more in the pipeline, and are looking to grow and evolve our business accordingly. This is an incredible opportunity to step into an exciting, early-stage company at the cutting edge of science with exceptional growth and market impact potential.


Multiomics is the future – come and join the biomodal team!


Your chance to lead a functional group in an exciting high growth biotechnology venture and make a real impact!


The Team

Our technology provides our customers with novel multi-modal information that will enable new scientific discoveries. Within the Computational Technology Department, Data Scientists are responsible for demonstrating the utility of our technology. They do this through the development of new methods to extract insights from the technology's output, and through collaboration with our customers to generate new scientific discoveries when they use the technology on their sample sets.


This is an exciting time for biomodal and we are looking to amplify our commercial activity and footprint into the future. World-leading researchers are working with us to demonstrate the utility of our current products and crystallise requirements for future products. We are rapidly expanding and evolving our workforce to support our early access customers and are preparing for broader customer adoption and new collaborations.


The Role

We are looking for an experienced bioinformatician / computational biologist, with prior experience leading a team, to head our Data Science group at biomodal (reporting to the VP of Computational Technology). This is a rare opportunity to lead a function that will really shape biomodal's product offerings and be at the interface with our early adopting customers. The individual will be responsible for building, developing, and managing the team as well as being hands-on and supporting key projects.


Key Responsibilities


  • Identify opportunities for innovative applications that leverage unique characteristics of our technologies and develop a roadmap to deliver new computational analysis methods to our customers
  • Collaborate with external partners to test the technology in their use cases and drive the collaborative work towards scientific publication
  • Design experiments to understand the utility of our technology in various aspects
  • Provide feedback to internal product development teams (molecular biology and bioinformatics software) to drive optimisation of our assays and bioinformatics pipelines
  • Interact with biomodal's customers to support their use of our technology to deliver on their research questions and to support ongoing product adoption
  • Respond to market and customer intelligence to rapidly prototype product and platform extensions and work with biomodal's development teams to transfer promising concepts into biomodal's portfolio.


The Person

The ideal candidate will be an experienced computational biologist with a demonstrable background leading or managing individuals, whilst still being technically credible and hands-on. We want someone who sees the opportunity implicit in this role, which is the chance to build something new and impactful in a company in its hyper-growth phase.


Essential Skills


  • A demonstrable track record of leading a team delivering complex computational biology projects or products to customers
  • Experience working collaboratively across organisations (e.g., industrial-academic collaborations, academic consortia, or cross-company collaboration) with demonstrable outcomes (publications or further funded work, etc.)
  • PhD or equivalent experience in a biological subject area, with a strong focus on informatics and data analysis
  • Detailed understanding of methods used in genomic data science, including experimental design, QC, and common analysis methods such as variant calling, QTL mapping, GWAS/EWAS
  • Enjoy working in a fast-moving, results-oriented business where delivery against deadlines is critical
  • Experience with applications of machine learning in genomics and computational biology
  • Ability to communicate complex topics effectively to diverse audiences
  • Experience with at least one programming language used in data science (Python, R, Julia)


Nice to Haves


  • Experience in preparing and defending scientific publications as first or corresponding author
  • Expertise in software development best practices (version control, code review, agile, testing, etc.)
  • Experience deploying systems on cloud platforms (GCP, AWS)
  • Experience with genomic workflow platforms (DNANexus, NextFlow)


This is an ideal opportunity for an experienced bioinformatics / computational biology leader to take the reins of a high-impact team in a business at an exciting stage of its evolution.


Benefits


  • Annual bonus scheme
  • Health and Life Insurance
  • Flexible/hybrid working conditions
  • Enhanced annual leave
  • Enhanced parental leave
  • 10% pension contribution


Seniority level


  • Director


Employment type


  • Full-time


Job function


  • Engineering and Information Technology


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