Associate Data Scientist

Associate Data Scientist role with USC supporting research across environmental health, exposomics, air pollution, and geospatial methods for life-course modeling of exposures and health impacts.

• Create, analyze, and interpret large datasets to support research objectives and solve analytic problems
• Build, test, and optimize statistical, predictive, and machine learning models
• Develop and deploy data pipelines, workflows, and automated processes with a focus on geospatial and remote sensing based work
• Collaborate with study investigators and staff to identify high-impact data applications and support decision-making
• Apply data science best practices to test, deploy, and iterate on analytic solutions
• Perform data manipulation, cleaning, and quality assurance to maintain data integrity
• Monitor project progress, track activities, and provide regular updates to the PI and study team on status and deliverables
• Draft reports, figures, and presentations that summarize analytic methodology and findings
• Keep current with new tools and methods in geospatial and data science, applying up-to-date techniques to ongoing research
• Maintain technical documentation and support continuous process improvement

• Bachelor’s degree in Applied Mathematics, Geography, Computer Science, Statistics, or a related quantitative field (or equivalent experience)
• 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 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

• Master’s degree or PhD in Geography, Statistics, Environmental Health, Remote Sensing, or a related field
• 5+ years of relevant experience in exposure data science, geospatial analytics, or a related field
• Experience using statistical computer languages (e.g., SAS, R, Python, SQL) to manipulate data and derive insights from large data sets, especially spatial data (e.g., Python, ESRI suite)
• Experience working with and creating data models and data architecture, plus experience with visualization tools (e.g., Tableau, ArcGIS, D3.js)
• Knowledge of current data modeling tools and machine learning techniques such as clustering, decision-tree learning, and artificial neural networks
• Proficiency with query languages (e.g., SQL, MDX) and experience across relational (MySQL, SQL Server, Snowflake, Redshift) and non-relational (MongoDB, No
  
  SQL, Mongo) databases and cloud environments
• Knowledge of applied statistical concepts and techniques including distributions, statistical testing, and regression
• Ability to write high-quality, well-documented SAS/Python code with familiarity in unit testing, source control, and code review
• Excellent written and oral communication skills, including summarizing findings for both technical and non-technical audiences
• Demonstrated interest in data science and artificial intelligence; open-domain contributions (e.g., Git Hub) and/or published writing in data science are a plus

• Python, SQL, SAS, R
• ESRI suite, Tableau, ArcGIS, D3.js
• MDX
• MySQL, SQL Server, Snowflake, Redshift
• MongoDB, No
  
  SQL, Mongo
• Git Hub, unit testing, source control, code review

• Los Angeles, CA (onsite)

• USD 99,823
  - USD 100,000 per year
• Annual base salary range: $99,823.75 - $

• Bachelor’s degree (minimum)
• Combined experience/education allowed as a substitute for minimum education

• 2 years