Data Analyst, Computational Immunology Specialist
5 days ago
Repertoire Immune Medicines is driving innovation in medical science by harnessing the remarkable power of the human immune system to treat cancer and autoimmune disease.
We are seeking a talented Data Scientist, Computational Biology to join our team and contribute to the discovery of new insights from our extensive and growing DECODE immune synapse database.
This role involves working at the interface of data analytics, data mining, statistics, bioinformatics, and machine learning with broad impact across early discovery, candidate development, and biomarker discovery.
As a member of our Computational Analytics Team, you will analyze large, multi-dimensional datasets and develop methods to identify and visualize signal in noise.
You will work alongside Computational Engineering, and interface directly with experimentalists in Platform Discovery, Immunology, and Protein Sciences to scope, build, and implement computational solutions.
The ability to work in a fast-paced, highly collaborative environment will be critical to success, as well as the ability to communicate effectively across various teams.
Key responsibilities include:
- Using statistical techniques to find relationships in complex biological data.
- Developing, evaluating, and implementing robust analytical methods/models/workflows/apps as needed for in-house discovery and development.
- Using analytical methods to identify patterns, signals, and features in highly multiplexed experimental assay data.
- Assisting in the conception, development, optimization, and assessment of machine-learning models.
- Maintaining familiarity with scientific literature to assist in the development and benchmarking of new methods.
- Building and deploying visualizations and user interfaces to be used by wet lab scientists.
- Supporting various teams for the processing and interpretation of next-generation sequencing (NGS) data and ensuring timely delivery of results.
- Maintaining high-quality documentation of work and discoveries, creating written reports, electronic lab notebooks, technical presentations for internal or external audiences, internal database records, code comments, and software documentation.
- Communicating key data insights to various audiences within R&D, as well as continuous project status updates, setbacks, and modifications of strategy.
- Managing and executing multiple projects across matrixed teams, working with leadership to meet short timelines while maintaining scientific rigor.
- Seeking out external resources and expertise when required.
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