Senior Scientist - Quantitative Genetics

Merck Group$94K — $144K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in Statistical Genetics, Computational Biology, Human Genetics, or related quantitative field
  • 2+ years post-PhD experience in pharma, biotech, or academic research
  • Hands-on expertise in quantitative/computational genetics methodologies
  • Experience with GWAS and various downstream genetic analyses
  • Familiarity with human genetics variant interpretation techniques

Responsibilities

  • Collaborate with data scientists in drug discovery to frame critical questions
  • Implement the appropriate human genetics methods across project stages
  • Conduct genetic safety assessments to predict adverse events
  • Perform rapid genetic due diligence for in-licensing opportunities
  • Integrate genetics with multi-omic data for target validation
  • Support pharmacogenomic analyses for clinical trial optimization
  • Develop automated tools for efficiency in genetic reviews

Benefits

  • Health insurance
  • Paid time off (PTO)
  • Retirement contributions
  • Sales or performance-based bonuses
Full Job Description
Your Role:

EMD Serono in Billerica, MA, is adding a Senior Scientist - Quantitative Genetics to their team. In this role you will employ human quantitative genetics to advance programs at all pipeline stages (target identification, target validation/assessment, safety de-risking, patient selection, indication selection and expansion, biomarker selection, in-licensing due diligence) in our neurology and immunology portfolio. You will work with other quantitative scientists as well as biologists, disease experts, and clinicians to deliver results that support program decision making.

To increase the impact of genetics on our pipeline, you will:
  • Collaborate with other data scientists in drug discovery/development program teams to ensure that the right questions are asked and answered. You will play a key role in performing analyses and explaining the results to other scientists.
  • Ensure we use the right human genetics methods at the right time.
  • Perform genetic safety assessments for pipeline targets, including loss-of-function carrier phenotyping, phenome-wide association analysis, and Mendelian randomization to anticipate mechanism-based adverse events and on-target toxicity.
  • Provide rapid genetic due diligence for in-licensing and business development targets (20-25 per year), assessing target-disease association, genetic safety signals, direction of effect, and competitive positioning.
  • Integrate genetic evidence with multi-omic data (proteomics, transcriptomics, eQTL/pQTL) for systems-level target validation and mechanism-of-action confirmation.
  • Support pharmacogenomic analyses for dose optimization, PK/PD modeling, and patient stratification strategies to enhance clinical trial design.
  • Automate genetics tools and reporting to support both quantitative experts and disease biologists. Focus on quick turnaround settings such as early target screening, search/in-licensing, and safety assessment. Integration with our agentic AI platform for scalable genetic reviews.
  • Work with engineering teams to develop interactive dashboards and visualizations to communicate genetic evidence to project teams, leadership, and due diligence committees.
  • Educate scientists across the R&D organization on the available methods and possibilities from human genetics.


Who You Are:

Minimum Qualifications:
  • PhD in Statistical Genetics, Computational Biology, Human Genetics, or other quantitative research discipline
  • 2+ years of experience post PhD in pharma, biotech, or academic research setting
  • 2+ years of experience in quantitative/computational genetics including hands-on implementation across a range of methods and technologies
  • 2+ years of experience with human genetics methods, including GWAS and downstream analyses (e.g., fine-mapping, enrichment, colocalization, eQTL/pQTL mapping, PRSs, Mendelian randomization, direction of effect determination, loss-of-function and gain-of-function analysis) as well as variant interpretation


Preferred Qualifications:
  • Demonstrated experience applying computational genetics to complex disease, with relevance to neurology and/or immunology
  • Strong quantitative and programming skills (e.g., Python and R in Unix/HPC environments, including biobank trusted research environments)
  • Proven ability to translate genetic analyses into clear, actionable recommendations for scientific and portfolio decisions
  • Experience with large scale biobank datasets such as the UK Biobank and All of Us as well as familiarity with disease-specific and multi-ethnic cohorts
  • Experience applying machine learning and AI methods to genomic and multi-omic datasets.


Pay Range for this position: $94,600 - $144,100

The offer range represents the anticipated low and high end of the base pay compensation for this position. The actual compensation offered will be determined by factors such as location, level of experience, education, skills, and other job-related factors. Position may be eligible for sales or performance-based bonuses. Benefits offered by the Company include health insurance, paid time off (PTO), retirement contributions, and other perquisites. For more information click here.

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