Research Senior Data Scientist - Ajami Lab - Department of Neurology (Remote)

Cedars-Sinai•West Hollywood, CA

12h•$117,100 - $198,900•Remote

About The Position

The Research Senior Data Scientist will help establish and advance an AI-driven computational research platform within the Ajami Lab in Cedars-Sinai’s Department of Neurology. The lab studies microglia and peripheral immune cells in neurodegenerative diseases, including ALS, Alzheimer’s disease, and Parkinson’s disease, using experimental models, single-cell and spatial multiomics, computational biology, and artificial intelligence. Working with data scientists, computational biologists, and experimental researchers, the incumbent will develop and apply AI and machine-learning approaches to integrate and interpret complex biological datasets. The work includes developing analytical frameworks, predictive models, and computational tools to identify disease-associated cellular states, molecular pathways, and potential therapeutic targets, and to generate testable biological hypotheses. Datasets may include single-cell and spatial transcriptomics, CITE-seq, spatial proteomics, and other multimodal data. The role also involves creating scalable, reproducible analysis pipelines and software; querying databases; cleaning and quality-checking data; applying statistical and machine-learning methods; deploying models; and communicating findings through scientific publications and conferences. The incumbent writes clean, reusable code managed on GitHub and serves as a resource to one or two staff members working on data-analysis algorithms, methods, and software.

Requirements

Bachelor’s degree in Computer Sciences, Machine Learning, Applied Mathematics, Econometrics, Statistics, Engineering, Physics, or a related field.
At least 5 years of professional experience in data science, healthcare, pharmaceutical industries, or universities working with biomedical, clinical, or biological data.
Intermediate or advanced programming proficiency in a high-level language such as R or Python.
Intermediate proficiency in SQL.
Experience developing and evaluating computational or statistical methods, including machine learning, for data analysis.
Experience as an author or co-author of at least one peer-reviewed scientific paper published in a journal.

Responsibilities

Invent, develop, evaluate, and apply computational and statistical methods, including artificial intelligence and machine-learning algorithms and software, for biomedical data analysis.
Create database-to-deployment model pipelines using programming languages including R, Python, SQL, and Neo4j.
Create sustainable data-science infrastructure and follow data-analysis standard methodologies.
Lead the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
Perform data cleaning, quality control, and analytical methods.
Conduct exploratory data analysis to assess the need for or appropriateness of advanced analytical methods.
Lead discussions with senior or lead research data scientists and principal investigators to identify biomedical research questions where data science can be applied.
Test and validate code, maintain adaptability of data applications, and use GitHub for version control.
Provide feedback to the lead for appraisals relating to research projects and work performance.
Develop AI-based analytical frameworks, predictive models, and computational tools to identify disease-associated cellular states, molecular pathways, and therapeutic targets and generate testable biological hypotheses.
Integrate single-cell and spatial transcriptomics, CITE-seq, spatial proteomics, and other multimodal datasets.
Develop scalable and reproducible AI/ML pipelines.
Collaborate with scientists on publications, grant applications, and new research initiatives.
Serve as a resource to one or two staff members in developing, evaluating, or applying algorithms, methods, and data-analysis software.