Senior Scientist, Statistical Genetics - 2443

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 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, you will be responsible for:

• Spearhead creative experimental approaches to leverage rare disease genetic data / learnings and large-scale population datasets, to understand the role of genetic variation in human disease and phenotypic variability
• Integrate information about regulatory mechanisms and other ‘omics data to characterize pathways and design innovative therapeutic strategies to address a range of severe diseases
• Leverage large-scale human genetic and ‘omic data to validate mechanism of action and characterize on-target risk for gene editing therapies
• Use rare disease and large-scale human genetic data to inform clinical trial design and genetic inclusion criteria
• Interpret and communicate findings to internal and external stakeholders to support pre-clinical decision-making with genomic insights
• Provide general genetic expertise to stakeholders across the organization to support preclinical, clinical, and commercial activities
• Work with members of research informatics team to ensure data integrity and well-documented, reproducible analysis

Requirements

Required Qualifications

The ideal candidate will possess:

• PhD in human genetics, statistical genetics, bioinformatics, data science, or related discipline and a minimum of 5-8 years of related experience (may include postdoctoral experience).
• Experience analyzing large-scale human genetic data with appropriate control for population structure and other possible confounders.
• Extensive experience in cloud computing (AWS); statistical programming with R, Python, or other programming language; tools for large-scale analyses (e.g. SAIGE, REGENIE, METAL/RAREMETAL, MAGMA/FUMA, Coloc/FastEnloc, 2SMR, etc.); and data visualization and interpretation.
• Knowledge of the full range of genome-wide and phenome-wide analysis approaches, encompassing genotype and sample quality control, phenotype evaluation, imputation, and approaches for well-calibrated association discovery in the presence of cryptic relatedness, population structure, extreme case-control imbalance, and sparse observations.
• Experience leveraging a broad range of publicly available databases to annotate data/results or supplement results interpretation from statistical analyses.
• Ability to identify, onboard, and leverage existing genetic and molecular datasets for rare disease patient cohorts and experimental models.
• Experience in polygenic score construction, validation, and application.
• Excellent attention to detail; oral and written communication; and time management skills.
• Ability to communicate complex concepts to audiences with a wide range of backgrounds and technical familiarity.
• Ability and desire to work in a fast-paced, interactive, and fluid environment in a multidisciplinary team focused on therapeutically-relevant genomic discovery.

Preferred Qualifications

Additionally, candidates with the following attributes are preferred:

• Experience analyzing UK Biobank data on Research Analysis Platform (DNAnexus RAP) strongly preferred.
• Experience analyzing RNA expression and proteomic data preferred.

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.