Associate Data Scientist

USC; Los Angeles (CA); On-site; USD 100,000 - 101,000; Full time

Job summary

USC invites applicants for an Associate Data Scientist role supporting environmental health research, exposomics, air pollution, and geospatial life-course modeling of exposures and health impacts. You will work with large datasets, build ML models, and deploy data pipelines in a geospatial context.

The position emphasizes collaboration with investigators, rigorous data cleaning, and clear communication of methods and findings.

Qualifications

• Bachelor’s degree in a quantitative field or equivalent experience.
• 2+ years in data science, data analytics, or related field.
• Proficiency in Python and SQL for data analysis/manipulation.
• Experience with relational/non-relational databases (e.g., MySQL, SQL Server, Snowflake, MongoDB).
• Experience cleaning, transforming, and validating data.
• Ability to derive actionable insights from datasets.
• Strong written and verbal communication skills.

Responsibilities

• 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 and workflows, with a focus on geospatial/remotely-sensed data.
• Collaborate with investigators and staff to identify high-impact data applications.
• Apply data science best practices to test, deploy, and iterate analytic solutions.
• Perform data cleaning and quality assurance to maintain data integrity.
• Monitor project progress and provide updates to the PI and study team.
• Draft reports, figures, and presentations summarizing methodologies and findings.
• Stay current with new geospatial/data science tools and methods.

Skills

Python

SQL

Data analysis

Geospatial

Communication

Education

Bachelor’s degree

Master’s degree

PhD

Tools

Python

SQL

SAS

R

Tableau

ArcGIS

D3.js

MySQL

SQL Server

Snowflake

Redshift

MongoDB

NoSQL

GitHub

Job description

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.

Responsibilities

• 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

Requirements

• 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

Preferred Qualifications

• 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, NoSQL, 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., GitHub) and/or published writing in data science are a plus

Technologies

• Python, SQL, SAS, R
• ESRI suite, Tableau, ArcGIS, D3.js
• MDX
• MySQL, SQL Server, Snowflake, Redshift
• MongoDB, NoSQL, Mongo
• GitHub, unit testing, source control, code review

Location

• Los Angeles, CA (onsite)

Salary

• USD 99,823 - USD 100,000 per year
• Annual base salary range: $99,823.75 - $100,000.00

Education

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

Minimum Experience

• 2 years