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About the role

You will join a growing team that provides support to Congenica’s innovation work leading the product development activities. The team is responsible for benchmarking existing bioinformatic analysis pipelines and for developing new pipelines and workflows that support detection, clinical prioritisation and therapy recommendation for genetic variants across a comprehensive range of DNA sequence variant types and platform technologies in rare disease and oncology. The team also plays a lead role in innovation working closely with the data science, artificial intelligence/machine learning and clinical teams.

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Who we are

Congenica is a pioneering digital health company enabling genomic medicine, revolutionizing the way genetic diseases are characterized and diagnosed, and providing life-changing answers.  Our end-to-end solutions, from sample to report, enable you to deliver world-class genomic medicine services and make important clinical decisions that transform the lives of patients and their families.

What you’ll be doing

Working at Congenica you will make a real impact on the lives of people around the world with rare diseases. Our products and services enable healthcare professionals to accurately, confidently and rapidly analyse complex genomic data and improve health outcomes.

What will you be responsible for?

  • The creation, development and improvement of genomic data analysis pipelines that operate at large scale (10,000s samples per year). This may include implementation of 3rd party software tools or writing of novel software to solve problems.
  • Benchmarking and performance assessment of variant calling and other bioinformatic analysis pipelines.
  • Provide the point of contact with the Product, Software Engineering and Clinical teams, customers and external experts to define requirements for innovations and product development activities.
  • Support statistical genetics expertise for the analysis of large data sets (e.g., UK Biobank, GWAS data)
  • Provide thought leadership for the company’s innovation activities, identifying novel inventions and improvements representing patentable opportunities.

Additional Responsibilities

  • Working with the CSO, developing and managing collaborative research programmes with external parties
  • Develop and submit applications for funding.
  • Manuscript preparation and presentation of research findings (internal and external meetings)
  • Processing, analysis and review of collaborator and customer data
  • Identification and review of key reference data required for product development and innovation activities.

What knowledge, skills and abilities will you need to succeed in this role?

Qualifications

  • Higher degree in Biological Sciences with demonstrable bioinformatics and programming skills and experience
  • We would consider a candidate with a degree in Computer Science with appropriate biological knowledge and expertise.

Knowledge, Skills & Abilities

  • Comprehensive knowledge and understanding of bioinformatics tools and principles for the analysis of genetic and genomics data.
  • Demonstrable programming skills in Python or R, with experience of writing novel pipelines for the analysis of biological data sets
  • Experience of working with large biological data sets.
  • Interaction with SQL databases such as bulk data entry, query, schema design and ORM
  • Unix environment
  • Awareness of software development principles
  • Demonstrable record of publications (peer-reviewed articles, white papers) and grant writing/funding

Behavioural Qualities

  • Excellent communication skills – ability to communicate complex biological and statistical concepts to non-experts.
  • Friendly, approachable and builds positive personal and organisational relationships.
  • Self-motivated and results-driven, problem-solver
  • Enthusiastic, hardworking, well organised and able to prioritise.
  • Able to work with others, and willing to contribute to team.

Great to haves

  • Analysis of RNA, protein, metabolic and microbiome data
  • Sound understanding of the principles of artificial intelligence and machine learning.
  • Commercial software development
  • Software development in an accredited/regulated environment
  • Experience working with Docker and Kubernetes.
  • Use of workflow managers such as Nextflow, Snakemake
  • Statistics and statistical genetics expertise
  • Experience of managing staff with diverse skill sets and work styles, supervision and mentorship of students.
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