Job Description

The Anatomic Pathology Group at our company's South San Francisco site is seeking a passionate and talented Data Scientist with experience in programming, data science, and tissue-based imaging. The successful candidate will join a dynamic digital pathology team to perform digital pathology analysis to support novel drug and biomarker development, particularly in oncology. Experience with datasets from Akoya Phenocycler and/or Vectra systems, as well as comfort with image analysis commercial software and/or open-source tools is highly desirable.

 Key Responsibilities:

• Analyze, visualize, and summarize molecular data from high-dimensional multiplexing IHC assays

• Perform custom data analyses on large datasets, and generate meaningful data visualizations to stakeholders

• Apply rigorous statistical methods and machine learning algorithms to analyze high-dimensional datasets

• Build end to end data visualization tools for non-programmer that help understand and interpret the complex high-dimensional data

• Develop models from datasets to identify associations for potential biomarker development and for further hypothesis testing

• Employ best reproducible research and data integrity practices to generate reusable analysis frameworks for imaging data

• Assist in the development and validation of digital pathology infrastructure solutions for large file management workflow

• Work proactively and collaboratively across disciplines, including pathologists, machine learning scientists, molecular biologists, protein scientists, bioinformaticians, and software engineers

Qualifications:

Education:

• Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Genetics, Mathematics, Molecular Biology, Statistics or related field and relevant experience listed below

Required Experience and Skills:

• Knowledge and experience in computational analysis for image-based histological or tissue-based assay readouts

• Demonstrated expertise in the application of methods of statistical learning and data mining for the integrative analysis of high-dimensional molecular datasets

• Previous experience with experimental design of biological assays, statistical hypothesis testing, and biological interpretation

• Strong programming skills in writing clean and scalable code with application in imaging (e.g. Python, MATLAB) and statistical analysis (e.g. R)

• Experience with data visualization software such as JMP, and PRISM; data visualization Python packages such as seaborn, matplotlib, etc.

• Demonstrate the ability to learn, be proactive and motivated, and consistently focus on details and execution

• Excellent oral and written communication skills

Preferred Experience and Skills:

• Skilled at integrating results generated from multiple omics data sources, and biological knowledge bases to customize analytical approaches for discovery research

• Experience applying AI / machine learning methods for analysis of image-based biological readouts

• High level of comfort with histology/microanatomy

• Experience with digital pathology image analysis software such as Halo, Visiopharm, QuPath, etc.

• Experience with computational analysis and biological interpretation of diverse large-scale experimental datasets (such as ssRNAseq, WES)

• Experience with good software development practices, collaborative software development, productionizing pipelines, and reproducible research principles

• Experience with version control environments, such as Git

• Experience with high-performance Linux cluster and cloud computing

• Experience working in cross-functional teams and in matrixed environments

#EligibleforERP 

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We are an Equal Opportunity Employer, committed to fostering an inclusive and diverse workplace.  All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status, or other applicable legally protected characteristics.  For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:
 

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U.S. Hybrid Work Model

Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.

The Company is required to provide a reasonable estimate of the salary range for this job in certain states and cities within the United States. Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education.

Expected US salary range:

Available benefits include bonus eligibility, long term incentive if applicable, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days. A summary of benefits is listed here.

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

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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. 

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