Senior Bioinformatics Scientist Job at Natera, Remote

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  • Natera
  • Remote

Job Description

Natera is seeking a Senior Bioinformatics Scientist to join our Bioinformatics Research team and help build the machine learning models behind Natera's tissue-free, methylation-based assay. These will be the models that detect cancer in the minimal residual disease (MRD) setting and help inform treatment selection. The ideal candidate brings a strong background in algorithm development, genomics, sequencing data processing, and applied machine learning. Primary Responsibilities: - Develop, train, and evaluate machine learning models, driving algorithm design decisions that support cancer detection in the MRD setting. - Own end-to-end research analyses, from ideation through implementation (scripts and notebooks), troubleshooting, and performance evaluation, including developing new features within existing pipelines. - Translate between wet-lab experimental design and computational analysis, navigating ambiguity as assay requirements evolve and maintaining rigorous quality control across high-volume sequencing data spanning multiple cohorts, vendors, and clinical protocols. - Communicate findings and model performance to both technical and cross-functional stakeholders, and contribute to establishing standards for code quality and reproducibility. Qualifications - Ph. D. in Bioinformatics, Computer Science, Engineering, Biochemistry, or a related field, with a strong focus on cancer epi/genomics with 0-3 years of professional experience. - Master in Bioinformatics, Computer Science, Engineering, Biochemistry, or a related field, with a strong focus on cancer epi/genomics with 4-6 years of professional experience. Knowledge, Skills, and Abilities: - Deep theoretical and practical understanding of high-throughput DNA sequence data analysis, including mapping, sequence alignment, and variant calling workflows. - Experience in algorithm development and data analysis, including applying and evaluating statistical methods. - Demonstrated experience in developing core ML models, including generalized linear models, kernel methods, tree-based algorithms, and neural networks, with a focus on biological data (e.

g. , DNA sequencing data) - Strong quantitative reasoning and data analysis skills, with a demonstrated ability to apply them effectively to relevant scientific problems. - Experience with Python and Linux command-line tools, including writing shell scripts. Strong computational and programming skills, including thorough experience with Python statistical packages (NumPy, Matplotlib, Pandas). - Familiarity with public databases such as TCGA, COSMIC, or OncoKB. - Ability to visualize findings and summarize results in oral and written form for both technical and non-technical audiences. - High scientific rigor, with eagerness to teach and learn new computational methods and biology. - Ability to work on a cross-functional team in a highly collaborative environment, partnering with both computational and experimental scientists. The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. Remote USA $117,400 — $146,800 USD OUR OPPORTUNITY Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly.

Job Tags

Work at office, Remote work

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