Memorial Sloan Kettering Cancer Center

Computational Biologist I, Clinical Data Mining (CDM)

Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in a related field with 2+ years of experience, or a Master's degree.
  • Proficiency in Python and/or R programming.
  • Working knowledge of SQL and relational databases.
  • Experience with machine learning and/or natural language processing methodologies.
  • Familiarity with source control using Git/GitHub.
  • Knowledge of cloud platforms or cloud-based data environments.
  • Strong communication skills for interacting with technical and non-technical stakeholders.

Responsibilities

  • Collaborate with various teams to support cancer research projects.
  • Develop data pipelines for integrating various healthcare datasets.
  • Build and deploy machine learning and NLP solutions for data curation.
  • Utilize large language models and AI technologies to enhance workflows.
  • Translate research questions into scalable computational solutions with cross-functional teams.
  • Support efforts to make clinical data accessible for research.
  • Contribute to the creation of cloud-based infrastructure for analytics.

Benefits

  • Full-time position with a 37.5-hour work week.
  • Hybrid work arrangement with 2 days onsite in New York, NY.
Full Job Description


In this role, you will collaborate with researchers, oncologists, data scientists, and engineers across MSK to develop machine learning (ML) and natural language processing (NLP) solutions that automate the extraction, standardization, and curation of clinically relevant data from unstructured sources. The mission of CDSI is to accelerate translational research by transforming real-world clinical data into high-quality, research-ready resources. Through the abstraction and integration of patient data from diverse clinical systems, CDSI enables clinicians, biologists, and computational scientists across the institution to access de-identified data that fuels discovery and innovation. Teams supporting CDSI have also developed widely adopted cancer research resources, including cBioPortal and OncoKB, which are used by thousands of researchers and clinicians worldwide.

As a Computational Biologist, your work will directly support institutional research projects, including enterprise curation, health disparities research supported by the Geoffrey Canada Center for Translational Cancer Disparities Research, and Cancer AI Alliance (CAIA) use cases. Through these efforts, you will help generate and curate data resources that power scientific discovery, advance cancer research, and ultimately improve patient outcomes.

Role Overview:

  • Partner with clinicians, researchers, engineers, and data scientists to support institutional cancer research initiatives.

  • Develop and maintain data pipelines to extract, transform, and integrate clinical, genomic, imaging, and other healthcare datasets.
  • Build and deploy machine learning (ML), natural language processing (NLP), and AI-based solutions for clinical data extraction and curation.
  • Leverage large language models (LLMs) and emerging AI technologies to improve data abstraction and research workflows.
  • Collaborate with cross-functional teams to translate research questions into scalable computational solutions.
  • Support enterprise curation efforts that make high-quality clinical data available to investigators across MSK.
  • Contribute to the development of cloud-based infrastructure and analytics tools supporting translational research.


Key Qualifications:
  • Bachelor's degree in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, Data Science, or a related discipline with 2+ years of relevant experience; or a Master's degree in a related field.
  • Experience programming in Python and/or R.
  • Working knowledge of SQL and relational databases.
  • Experience applying machine learning and/or NLP methodologies.
  • Experience working with source control systems such as Git/GitHub.
  • Experience using cloud platforms or cloud-based data environments.
  • Strong communication and collaboration skills with both technical and non-technical stakeholders.


Preferred Qualifications:
  • M.S. or Ph.D. in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, or a related field.
  • Experience building and deploying machine learning models in research or production environments.
  • Knowledge of NLP methodologies and AI-driven applications.
  • Experience with large language models (LLMs), prompt engineering, and AI APIs.
  • Familiarity with healthcare, clinical research, bioinformatics, cancer genomics, or clinical informatics.
  • Experience with cloud technologies such as AWS, Azure, Google Cloud Platform, or Databricks.
  • Experience working with electronic health records (EHRs), clinical data warehouses, or healthcare datasets.


Core Skills:

  • Passion for applying computational methods to cancer research.
  • Strong analytical and problem-solving abilities.
  • Experience collaborating across multidisciplinary teams.
  • Effective communication skills with technical and non-technical audiences.
  • Interest in AI, machine learning, and clinical data science.
  • Adaptable, self-motivated, and eager to learn.
  • Ability to manage multiple priorities in a fast-paced environment.


Additional Information:
  • Schedule: Full-time, 37.5 hours per week
  • Location: 323 East 61st Street, New York, NY (Hybrid, 2 days onsite)
  • Reporting To: Senior Computational Biologist II


Helpful Links:
  • Compensation Philosophy
  • Benefits


Pay Range: $83,800.00 - $134,000.00

FSLA Status: Exempt

About Memorial Sloan Kettering Cancer Center

Memorial Sloan Kettering Cancer Center is a world-renowned cancer treatment and research institution located in New York City. The center was founded in 1884 and has since become one of the leading cancer centers in the world, with a focus on patient care, research, and education. Memorial Sloan Kettering Cancer Center employs over 20,000 people, including doctors, nurses, researchers, and support staff, and treats over 500,000 patients each year. The center is known for its innovative treatments and cutting-edge research, which has helped to improve the lives of cancer patients around the world. Memorial Sloan Kettering Cancer Center is committed to finding a cure for cancer and improving the quality of life for cancer patients everywhere.
Learn more about Memorial Sloan Kettering Cancer Center
Size
20,000 employees
Industry
Founded
1884

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