Associate Director, Data Science, Computational Oncology

MSD; Boston (MA); Hybrid; USD 160,000 - 251,000; Full time

Job summary

MSD in Boston seeks an Associate Director of Data Science in Computational Oncology to lead analyses of oncology genomics data and guide target nomination and biomarker discovery.

You will work with a cross-disciplinary team to apply statistics, ML, and AI for decision-grade insights while collaborating with experimental and software colleagues.

Qualifications

• PhD/MS/BS with strong quantitative background in computational biology or genomics.
• Deep experience analyzing large-scale NGS datasets (bulk RNA-seq, WES/WGS, scRNA-seq).
• Proven ability to apply machine learning to biological data with thoughtful judgment.

Responsibilities

• Analyze large-scale oncology datasets (bulk RNA-seq, WES/WGS, scRNA-seq) to understand disease biology.
• Nominate and prioritize drug combinations by integrating multi-omics evidence and biology.
• Apply rigorous statistics and multi-omics integration to reach robust conclusions.
• Apply deep learning and foundation models to cell-type deconvolution, batch integration, and patient stratification.
• Leverage AI, including LLMs, to accelerate evidence synthesis and analysis in a collaborative setting.
• Collaborate across disciplines to translate preclinical findings into patient biology.

Skills

R or Python

Statistics

Machine learning

Git

Linux

AWS

Nextflow

Databricks

Posit

Education

PhD in computational biology or related

MS in a quantitative STEM discipline

BS with 12+ years relevant experience

Tools

AWS

Nextflow

Databricks

Posit

Job description

Associate Director of Data Science, Computational Oncology (R4)

Translational Genome Analytics (TGA) / Data, AI and Genome Sciences (DAGS)

Location: Boston, MA (hybrid)

Our company is a global health care leader committed to being the world's premier, most research-intensive biopharmaceutical company. Our Research Laboratories take our leading discovery capabilities and world-class small molecule and biologics research and development expertise to create breakthrough science that radically changes how we approach serious diseases.

The Data, AI and Genome Sciences (DAGS) department seeks a talented data scientist with a strong quantitative and statistical foundation to join our Translational Genome Analytics (TGA) team in Boston, MA. In this role, you will bring rigorous statistics, machine learning, and modern AI to large, complex multi-omics and functional genomics datasets to understand the molecular basis of cancer and to nominate targets and biomarkers across our research portfolio. You will work closely with computational, AI and ML, and experimental colleagues to turn data into decisions that move programs forward. We are especially interested in scientists with a strong oncology and cancer genomics background who can also analyze functional genomics screens, so you can support target nomination and the broader discovery portfolio from both directions.

You are an independent scientist who takes an open-ended question and carries it through to a clear answer, and who thrives in a highly collaborative discovery environment.

In This Exciting Role, You Will

• Analyze large-scale oncology datasets, including bulk RNA-seq, whole-exome and whole-genome sequencing (WES/WGS), and single-cell RNA-seq (scRNA-seq), to understand disease biology and the mechanisms of disease progression and drug action.
• Analyze functional genomics and perturbational screens, including pooled and arrayed CRISPR screens and Perturb-seq, from QC and hit calling through biological interpretation, to establish target dependency and mechanism for programs across therapeutic areas.
• Nominate and prioritize drug combinations for both oncology and immunology disease areas by weighing expression profiling, disease biology, mechanistic and functional-genomics evidence, and the competitive landscape together, and bring that evidence to program teams across the portfolio.
• Apply rigorous statistics and integrate multi-omics and functional genomics data with prior biological knowledge, using network-based and machine learning approaches, to reach robust conclusions and a coherent picture of target and pathway biology.
• Apply deep learning and single-cell foundation models to problems such as cell-type deconvolution, batch integration, patient stratification, and perturbation-response prediction.
• Use modern AI, including LLM-based agents and retrieval over internal data, to accelerate evidence synthesis and analysis, and help bring these tools into routine, well-validated use.
• Draw on human and real-world data to inform and reverse-translate discovery hypotheses, connecting preclinical findings to patient biology.
• Collaborate closely across disciplines, including experimental scientists, AI and ML and data science teams, software engineers, and program teams, and set a high bar for reproducible, well-documented research that supports Discovery Oncology.

Minimum Requirements

• A PhD in computational biology, bioinformatics, biostatistics, genetics/genomics, computational biology, mathematics, computer science, biophysics, computational chemistry or a related quantitative STEM discipline and 0+ years of relevant experience; MS and 8+ years of relevant experience; OR BS and 12+ years of relevant experience.
• A passion for solving problems in oncology and cancer genomics through computational methods, with a consistent focus on detail and execution.
• Deep experience analyzing and biologically interpreting large-scale NGS datasets (bulk RNA-seq, WES/WGS, scRNA-seq), including experimental design, QC, and building analyses where no standard pipeline exists, and integrating multiple omics layers with prior biological knowledge.
• A strong statistical foundation, spanning hypothesis testing, regression and mixed models, survival analysis, and dimensionality reduction, with sound judgment about confounding, batch effects, and multiple comparisons, and a track record of applying machine learning to biological data with judgment about where it adds value and where simpler methods suffice.
• Strong technical skills, including R or Python, version control (Git), and Linux, with hands-on experience across cloud and data platforms such as AWS (S3), Nextflow, Databricks, and Posit.
• Familiarity with major cancer genomics resources, such as TCGA, GTEx, CCLE, CPTAC, and DepMap.
• A collaborative working style and excellent oral and written communication skills.

Preferred Experience and Skills

• A Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Statistics, Computer Science, Genetics, Mathematics, or a related field.
• Post-doctoral or relevant industry experience in cancer genomics or computational oncology, with a deep understanding of cancer biology and current research trends.
• Substantial computational experience with functional genomics data, including CRISPR screen hit-calling frameworks, library design, optical or single-cell screens, and image-based phenotypic profiling.
• Experience applying or fine-tuning foundation models for single-cell or genomic data, and an interest in developing agentic AI and LLM-powered tools for biological analysis.
• Network-based analysis of gene regulatory patterns and signaling pathways from NGS data.
• A strong publication record.

Travel

Up to 10% travel is required.

US and Puerto Rico Residents Only

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities.

Equal Employment Opportunity

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit: EEOC Know Your Rights EEOC GINA Supplement

We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

Learn more about your rights, including under California, Colorado and other US State Acts

The salary range for this role is $159,600.00 - $251,200.00. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

Employee Status: Regular

Relocation: Domestic

VISA Sponsorship: Yes

Travel Requirements: 10%

Flexible Work Arrangements: Hybrid

Shift: Not Indicated

Valid Driving License: No

Hazardous Material(s): n/a

Job Posting End Date: 10/5/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.