KC214 - Senior Translational Data Scientist

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Posted: 20/05/2019 11:48
Start Date: Not Available
Salary: Competitive
Location: Babraham Research Campus, Cambridge, UK
Level: Scientific
Deadline: 20/09/2019 23:59
Hours: 35.00
Benefits: Excellent Range of Benefits
Job Type: Permanent

Kymab is a clinical-stage biopharmaceutical company developing a deep pipeline of novel antibody-based therapies in a broad range of indications. The Company generates its product candidates using its proprietary, integrated platforms collectively called IntelliSelect®. Kymab’s platforms have been designed to maximize the diversity of human antibodies produced in response to immunization with antigens. Selecting from a broad diversity of fully human antibodies allows for the identification of antibodies with optimal drug-like properties.

We are looking to recruit an outstanding Translational Data Scientist to join our translational science team.  You will have the opportunity to analyse large data sets and influence the development of the company’s technology strategy. Supporting and advising our development team in bioinformatics and statistical approaches you will help inform optimal decision making in Kymab’s translational sciences efforts to support our clinical trial strategy.  You will need to work closely with a multidisciplinary team to develop first-in-class drug discovery technology.

Key Duties/Responsibilities:

  • Analysing proprietary pre-clinical/clinical and public dataset to advance our knowledge on disease and targets of interest

  • Interacting with external CRO and academic collaborators dealing with bioinformatic data analysis 

  • Identifying clinical biomarkers and strategies that help driving Kymab’s clinical development decisions.

  • Collaborate with scientists and clinicians from Kymab’s therapeutic areas and Kymab’s development team for our post-DC projects, to design experiments and establish data analytical plans for bioinformatics related activities and multi-omics data integration.

  • Analyse of in-house generated (preclinical and clinical ) datasets and public data to support drug candidates’ clinical development (identification of right patient/right indication, predictive and response biomarker discovery and clinical data analysis and integration)

  • Generate and review presentations for “internal” project team meetings, collaborators and governance teams. Also communicate research results through conference presentations, scientific publications, or project reports (including documents for regulatory submission).

  • Develop and maintain data models and databases.

  • Implement and develop analysis pipelines using cutting-edge algorithms and statistically sound methodologies

  • Support patent filings where appropriate.


Education & Experience

  • PhD or Master or equivalent degree in bioinformatics, biostatistics, computational biology, machine learning, data science or related field.

  • >5 years of experience in analysing large biological datasets relevant to drug discovery in industry or relevant academic setting, expert knowledge of statistical programming. Experience in other numerical/biological scientific discipline will be considered.

  • Experience in analysing public genomic, transcriptomic and proteomics datasets (e.g TCGA, 100000 genome etc…)

Skills & Knowledge


  • Solid understanding of biostatistics. Deep understanding of probabilistic and statistical modelling, and data mining algorithms, algorithm design and data structures

  • Proven working experience with R, Python and SQL (or similar scripting programming language) a must.

  • Ability to collect, organise and analyse large molecular datasets such as raw microarray data, NGS (RNA-seq and whole exome-seq) including experience with single cell sequencing data and proteomics data for basic research purposes or clinical samples analysis.

  • Interest in designing and applying bioinformatics algorithms including unsupervised and supervised machine learning, dynamic programming, distributed computing or graphic algorithms.

  • Excellent communication and presentation skills; Team spirit and commitment to share and collaborate

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