Bioinformatics Analyst | Remote NGS Data Science Specialist

As a Bioinformatics Analyst, you'll collaborate with world-class scientists on groundbreaking projects that bridge computational biology and data science. You'll exercise considerable autonomy in designing and refining bioinformatics pipelines while enjoying the flexibility of remote work (with just one in-person day weekly at our Cambridge, USA facility). Key Responsibilities - Design and implement computational strategies for analyzing large-scale biological datasets, including genomics, transcriptomics, proteomics, and metabolomics. - Develop robust, scalable bioinformatic workflows for processing NGS data, with particular emphasis on single-cell and bulk RNA-seq analysis. - Collaborate directly with clients to understand research objectives and transform them into actionable bioinformatics solutions. - Apply statistical modeling, machine learning algorithms, and data mining techniques to uncover patterns and biomarkers within complex biological data. - Execute rigorous quality control protocols, perform sequence alignment to reference genomes, and conduct variant calling with precision. - Generate and optimize joint-genotyped VCF files for downstream analytical applications. - Craft custom algorithms addressing unique computational challenges in biological data processing. - Communicate analytical findings to diverse audiences—from technical specialists to non-technical stakeholders. - Remain at the forefront of emerging bioinformatics methodologies; contribute substantively to continuous improvement initiatives. - Integrate and analyze both short and long-read sequencing data through meticulously optimized workflows. Required Skills and Qualifications - Bachelor's or Master's degree in Bioinformatics, Computational Biology, Computer Science, or related field. - Minimum 3 years of hands-on experience with NGS workflow development and analysis. - Demonstrable proficiency with GxP standards, Genedata Selector 2023, and NGS applications in Cell Therapy domains. - Comprehensive understanding of bioinformatics principles, algorithms, and analytical tools. - Proven track record analyzing high-throughput genomic, transcriptomic, or proteomic data. - Extensive experience creating and optimizing single-cell and bulk RNA-seq data processing pipelines. - Advanced capabilities in pipeline development utilizing Nextflow (DSL2), Cromwell, or comparable frameworks. - Strong Python programming skills (Python 3.9+) with specific application to bioinformatics challenges. - Robust understanding of statistical analysis, machine learning algorithms (including deep learning), and data mining approaches. - Excellent written and verbal English communication skills (C1 level or higher). - Ability to work independently in a remote environment while maintaining high productivity. - Willingness to visit Cambridge, USA office at least once weekly. Nice to Have - Experience with next-generation sequencing (NGS) variant calling and interpretation using tools like GATK4, DeepVariant, or VarScan2. - Knowledge of structural bioinformatics principles and molecular modeling techniques. - Familiarity with AWS cloud deployment (EC2, S3, Batch) for bioinformatics pipelines. - Experience with big data analysis frameworks (Spark, Dask) relevant to biological data processing. - Background implementing containerized solutions (Docker, Kubernetes) for reproducible research. - Proficiency in R programming (R 4.2+) for advanced statistical analysis. - Demonstrated ability to communicate complex bioinformatic concepts to non-specialized audiences. - Publications in peer-reviewed journals related to computational biology or bioinformatics. Why Join Our Team Become part of a forward-thinking organization that values innovation and scientific excellence. You'll operate at the frontier of bioinformatics—utilizing state-of-the-art technologies and contributing to significant advances in biological research. We offer competitive compensation, flexible remote work arrangements, professional development opportunities, and the chance to collaborate with leading experts in the field. This position strikes the perfect balance between autonomy and teamwork in an environment committed to advancing bioinformatics research and applications.