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Keck Medicine of USC·Los Angeles, CA

Associate Data Scientist

Full time
iPosting details
ScheduleFull time
EducationMaster's degree preferred · Doctorate preferred
Experience5+ years preferred
SourceKeck Medicine of USC · posted Oct 9, 2026
✓Requirements
Education
✓Bachelor’s degree in Applied Mathematics, Geography, Computer Science, Statistics, or a related quantitative field (or equivalent experience)
✓Bachelor's degree
Master's degree or PhD in Geography, Statistics, Environmental Health, Remote Sensing, or a related field preferred
Bachelor's degree In Applied Mathematics Or Computer Science Or Statistics Or in related field(s) preferred
Qualifications
✓Minimum 2 years of experience in data science, data analytics, or a related field
✓Proficiency in Python and SQL for data analysis and data manipulation
✓Experience working with relational and/or non-relational databases (e.g., MySQL, SQL Server, Snowflake, MongoDB)
✓Experience performing data cleaning, transformation, and validation
✓Demonstrated ability to analyze datasets and deliver actionable insights
✓Strong written and verbal communication skills
✓Addtional Education Requirements Combined experience/education as substitute for minimum education
✓2 years
✓Experience using statistical computer languages (e.g., R, Python, SQL) to manipulate data and draw insights from large data sets.
✓Knowledge of current data modeling tools and various machine-learning techniques and algorithms (e.g., clustering, decision-tree learning, artificial neural networks).
✓Experience scripting and programming in several languages with common data science toolkits.
✓Proficient use of query languages (e.g., SQL, MDX) and experience working with relational (e.g., MySQL, SQL Server, Oracle, Snowflake, Redshift) and non-relational (e.g., Mongo, NoSQL) databases.
✓Knowledge of applied, statistical concepts and techniques skills (e.g., distributions, statistical testing, regression).
✓Ability to provide both detailed information and summaries to management-level individuals and groups.
✓Experience developing customer relationships and delivering customer-focused service.
✓Proven problem-solving and decision-making skills, and the ability to uncover root cause and evaluate different solution options.
5+ years of relevant work experience in exposure data science, geospatial analytics, or a related field preferred
Experience using statistical computer languages (e.g., SAS, R, Python, SQL) to manipulate data and draw insights from large data sets especially spatial data sets (e.g. Python, ESRI suite) preferred
Experience working with and creating data models and data architecture, and using data visualization tools (e.g., Tableau, ArcGIS, D3.js) preferred
Knowledge of current data modeling tools and machine-learning techniques (e.g., clustering, decision-tree learning, artificial neural networks) preferred
Proficiency with query languages (e.g., SQL, MDX) and experience with relational (e.g., MySQL, SQL Server, Snowflake, Redshift) and non-relational (e.g., MongoDB, NoSQL) databases and cloud environments preferred
Knowledge of applied statistical concepts and techniques (e.g., distributions, statistical testing, regression) preferred
Ability to write high-quality, well-documented SAS/Python code, with familiarity in unit testing, source control, and code review preferred
Excellent written and oral communication skills, including the ability to summarize findings for both technical and non-technical audiences preferred
Demonstrated interest in data science and artificial intelligence; open-domain contributions (e.g., GitHub) and/or published writing in data science are a plus preferred
4 years preferred
+Keck Medicine of USC
Los AngelesCA
Pay for this position
Employer-posted
$100k/yr
Apply to Keck Medicine of USCContact Recruiter about this role
✓You’ll need
Education
✓Bachelor’s degree in Applied Mathematics, Geography, Computer Science, Statistics, or a related quantitative field (or equivalent experience)
✓Bachelor's degree
Master's degree or PhD in Geography, Statistics, Environmental Health, Remote Sensing, or a related field preferred
Bachelor's degree In Applied Mathematics Or Computer Science Or Statistics Or in related field(s) preferred
Qualifications
✓Minimum 2 years of experience in data science, data analytics, or a related field
✓Proficiency in Python and SQL for data analysis and data manipulation
✓Experience working with relational and/or non-relational databases (e.g., MySQL, SQL Server, Snowflake, MongoDB)
✓Experience performing data cleaning, transformation, and validation
✓Demonstrated ability to analyze datasets and deliver actionable insights
✓Strong written and verbal communication skills
✓Addtional Education Requirements Combined experience/education as substitute for minimum education
✓2 years
✓Experience using statistical computer languages (e.g., R, Python, SQL) to manipulate data and draw insights from large data sets.
✓Knowledge of current data modeling tools and various machine-learning techniques and algorithms (e.g., clustering, decision-tree learning, artificial neural networks).
✓Experience scripting and programming in several languages with common data science toolkits.
✓Proficient use of query languages (e.g., SQL, MDX) and experience working with relational (e.g., MySQL, SQL Server, Oracle, Snowflake, Redshift) and non-relational (e.g., Mongo, NoSQL) databases.
✓Knowledge of applied, statistical concepts and techniques skills (e.g., distributions, statistical testing, regression).
✓Ability to provide both detailed information and summaries to management-level individuals and groups.
✓Experience developing customer relationships and delivering customer-focused service.
✓Proven problem-solving and decision-making skills, and the ability to uncover root cause and evaluate different solution options.
5+ years of relevant work experience in exposure data science, geospatial analytics, or a related field preferred
Experience using statistical computer languages (e.g., SAS, R, Python, SQL) to manipulate data and draw insights from large data sets especially spatial data sets (e.g. Python, ESRI suite) preferred
Experience working with and creating data models and data architecture, and using data visualization tools (e.g., Tableau, ArcGIS, D3.js) preferred
Knowledge of current data modeling tools and machine-learning techniques (e.g., clustering, decision-tree learning, artificial neural networks) preferred
Proficiency with query languages (e.g., SQL, MDX) and experience with relational (e.g., MySQL, SQL Server, Snowflake, Redshift) and non-relational (e.g., MongoDB, NoSQL) databases and cloud environments preferred
Knowledge of applied statistical concepts and techniques (e.g., distributions, statistical testing, regression) preferred
Ability to write high-quality, well-documented SAS/Python code, with familiarity in unit testing, source control, and code review preferred
Excellent written and oral communication skills, including the ability to summarize findings for both technical and non-technical audiences preferred
Demonstrated interest in data science and artificial intelligence; open-domain contributions (e.g., GitHub) and/or published writing in data science are a plus preferred
4 years preferred
+Benefits
Continuing education
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About the role

The Department of Population and Public Health Sciences at the University of Southern California (USC) invites applications for an Associate Data Scientist position supporting research in environmental health, exposomics, air pollution, and geospatial methods for modeling environmental and extreme weather-related exposures and their health impacts across the life course.

What you’ll do
Create, analyze and interpretCreate, analyze and interpret large datasets to support research goals and solve data analytic problems
Build, test, and optimizeBuild, test, and optimize statistical, predictive, and machine learning models
Develop and deploy dataDevelop and deploy data pipelines, workflows, and automated processes especially geospatial and remote sensing based
Partner closely with studyPartner closely with study investigators and staff to identify high-impact data applications and support effective decision-making
Apply data science bestApply data science best practices to test, deploy, and iterate on analytic solutions