Job Information
Editas Medicine Senior Scientist I, Statistical Genetics in Cambridge, Massachusetts
At Editas, we’re driven by a collective purpose, to bring transformative and life changing therapies to people living with serious diseases with the greatest unmet needs. This fuels our drive to excel in scientific innovation, allowing us to harness the power and potential of CRISPR/Cas9 and CRISPR/Cpf1 (Cas12a) gene editing.
We believe our people are at the core of everything we do, and we’re committed to cultivating a culture where every individual feels valued and included. To do this, we strive to integrate belonging, inclusivity, diversity, and equity into every aspect of our organization.
Together, we are leading the way towards a healthier and more equitable future.
Position Summary
The Human Genetics and Genomics group at Editas Medicine is seeking a passionate scientist to lead the analysis of human genetic and ‘omic data to identify and validate targets and support development of CRISPR-based gene editing therapies. This individual will design and execute experiments that leverage rare-disease patient datasets, large-scale human genetic datasets (e.g. UK Biobank), catalogs of disease mutations (e.g. OMIM, ClinVar), and molecular data (e.g. RNA expression, proteomics) to understand the genetic etiology of severe diseases; identify therapeutic mechanisms amenable to Editas’ gene editing strategies; and characterize patient populations amenable to treatment. The individual will work collaboratively with peers in Human Genetics and Genomics, Computational Biology, Discovery, and Translational Sciences to advance early research and translational activities. This is an exciting opportunity to contribute to the development of cutting-edge precision genetic therapeutics for diseases with substantial unmet clinical need.
Key Responsibilities
As the Senior Scientist, Statistical Genetics, you will be responsible to:
Design and execute statistical analyses leveraging large-scale biobank data and/or rare disease genetic datasets, to understand the role of genetic variation in human disease and identify candidate therapeutic targets.
Integrate information from various genetics and ‘omics data sources to characterize regulatory mechanisms and pathways, design innovative therapeutic strategies to address a range of severe diseases, and characterize on-target risk for the proposed therapies.
Identify and onboard existing and new genetic and molecular datasets for disease cohorts and experimental models.
Contribute to building statistical genetics analysis capabilities, pipelines, and modules to enable high-throughput and reproducible analyses.
Collaborate with members of the statistical genetics and research informatics teams to implement methods to efficiently query large-scale human genetic data, ensure data integrity, and execute well-documented, robust and reproducible analyses.
Stay up to date with emerging methods, resources and developments in the field, and identify opportunities to expand or improve our capabilities to advance our pipeline.
Interpret, communicate results, and recommend next steps to internal and external stakeholders to support decision making with genomic insights.
Provide statistical genetics expertise to stakeholders across the organization.
Requirements
Required Qualifications
The ideal candidate will possess:
Master’s or PhD in statistical genetics, bioinformatics, genetic epidemiology, biostatistics, computational biology or related discipline; and a minimum of 4 years post-PhD or 8 years post-Masters experience leveraging human genetics data.
Strong foundation in applied statistics, population genetics, genetic association studies and computational approaches.
Extensive experience in using a wide range of genome-wide and phenome-wide analysis approaches (e.g. GWAS, PheWAS, PRS, rare variant burden tests), software (e.g. REGENIE, PLINK, VCFtools) and databases (e.g. gnomAD, OMIM, GTEx, ENCODE) to elucidate causal disease associations.
Technical skills to handle and manipulate large-scale datasets and execute high-throughput analyses of genetic and clinical data; familiarity with large biobank data (e.g. UK Biobank).
Experience with post-GWAS analyses (e.g. variant annotation, fine mapping, pathway enrichment), data visualization, and leveraging a broad range of publicly available datasets to annotate results and help with result interpretation.
Proficiency in a statistical programming language (R or Python preferred) and Unix/Linux shell scripting, experience in AWS cloud computing environment, code management and version control.
Excellent attention to detail; time management, problem-solving and self-learning skills.
Ability to communicate complex concepts to audiences with a wide range of backgrounds and technical familiarity.
Ability and desire to work both independently and collaboratively in a fast-paced, interactive, fluid environment in a multidisciplinary team.
Preferred Qualifications
Additionally, one or more of the following attributes is a plus:
Hands on experience analyzing UK Biobank data, and experience working on the DNAnexus Research Analysis Platform (RAP) strongly preferred.
Familiarity working in JupyterLab and Spark cluster environments, performing SQL queries.
Ability to implement bioinformatics workflows and pipelines for high-throughput analyses.
Experience working with other ‘omics data types (e.g. RNAseq, scRNAseq, CHIP-seq, proteomics, …)
Familiarity with supervised and unsupervised machine learning methods and applications.
Previous experience in applying human genetic analyses to target identification and validation.
Benefits
Benefits Summary:
Editas provides a comprehensive array of benefits to all employees, including a Blue Cross Blue Shield PPO Medical Plan, a company-funded Health Savings Account, Dental and Vision Insurance, Life and Disability Insurance, Dependent Care Account, Tuition Reimbursement, 401(k) plan with company match, Employee Stock Purchase Plan, Employee Assistance Plan, Wellness Programs, and a flexible Paid Time Off policy.
If you are a results-focused and collaborative professional with a passion for advancing transformative therapies, we invite you to apply. Join us at the forefront of genetic innovation and be a key contributor to Editas Medicine's mission of redefining healthcare through cutting-edge genetic technologies.
Fostering Belonging. Fueling Innovation. Transforming Lives.