Job DescriptionThe Translational Genome Analytics group within the Data, AI & Genome Sciences Department is recruiting a Director of Oncology Data Scientist to join our multi-modal biomarker discovery team. We are seeking an experienced and innovative computational scientist to perform data mining of multi-modal tumor profiling datasets and inform decisions across all stages of our company's expanding oncology pipeline.
The successful candidate will:
- Enable reverse translation from large multi-modal clinical datasets to inform biomarker discovery and combination strategies in molecularly defined patient populations with high unmet medical need.
- Analyze, summarize and visualize the findings from large multi-modal clinico-genomic datasets which include bulk RNAseq, WES/WGS, imaging, epigenetic profiling, single-cell RNAseq, and proteomics data from oncology clinical trials and real-world datasets.
- Leverage advanced deep learning and AI methods and multivariate predictive modeling to discover novel biomarkers predictive of clinical outcomes.
- Effectively collaborate with AIML teams working on development of foundation models trained on large cohorts of human data.
- Present data analyses to inform and interact with stakeholders representing a wide span of internal organizations, including early discovery, translational and clinical development teams.
QUALIFICATIONS:Education:- Ph.D. in quantitative discipline such as Engineering, Applied Physics/Mathematics, Bioinformatics, Computational Biology or related field with a significant computational and statistical component and six (6) years of relevant experience in pharma, biotech or academic setting.
Required Experience and Skills:- Experience in applying computational methods in cancer biology.
- Demonstrated expertise in the application of methods of statistical learning and data mining to the integrative analysis of multimodal, high-dimensional tumor profiling datasets in the oncology and immuno-oncology context.
- Hands-on analysis experience with the application of machine learning algorithms to large clinico-genomic, genetic and immunogenomic real-world and clinical trial datasets.
- Extensive experience and demonstrated expertise to code in scientific computation environments with adoption of best practices for reproducible data analyses.
- Strong communication and presentation skills; ability to guide and influence decisions through use of data-driven hypotheses; attention to detail.
- Independent, flexible and collaborative mindset
Preferred Experience and Skills:- Demonstrated experience with analysis of large-scale multi-modal data originating from clinical trials and real-world datasets.
- Deep understanding of the major concepts of cancer biology as represented in multi-modal molecular and imaging data.
- Experience within a matrixed industry environment and ability to effectively collaborate with colleagues from a wide range of disciplines.
- Record of publishing in high profile scientific journals
#EligibleforERP
Required Skills: Cancer Genomics, Cancer Research, Computational Methods, Data Science, High Dimensional Data Analysis, Immuno-Oncology, Machine Learning (ML), Multimodal, Multimodal Analysis, Oncology, Real World Data, Statistical Learning
Preferred Skills: Current Employees apply HERE
Current Contingent Workers apply HERE
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. Please click here if you need an accommodation during the application or hiring process.
The salary range for this role is
$236,000.00 - $371,500.00
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.
You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.
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
Search Firm Representatives Please Read Carefully Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
Employee Status: Regular
Relocation:Domestic/International
VISA Sponsorship:Yes
Travel Requirements:10%
Flexible Work Arrangements:Not Applicable
Shift:1st - Day
Valid Driving License:No
Hazardous Material(s):n/a
Job Posting End Date:07/24/2026
*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. 
