Prepare, clean, and structure time-series and geospatial datasets for machine learning workflows
Perform feature preparation including temporal alignment, resampling, lag features, and spatial associations
Ensure datasets are free from common ML issues such as misaligned timestamps, or invalid labels
Validate data quality through consistency checks, anomaly detection, and edge-case analysis
Document dataset assumptions, preprocessing steps, and known limitations for ML handoff
Support ML engineers during model development, assessment, and deployment
Collaborate with team members using notebooks and version-controlled workflows

Requirements

Bachelor’s or Master’s degree in a STEM discipline (e.g., engineering, computer science, physics, applied mathematics, statistics, geoscience, or related field)
Strong proficiency in Python, particularly for data analysis and preprocessing
Ability to reason through data problems using a structured, analytical approach
Clear written and verbal communication skills
U.S. Citizenship required.
Experience or be willing to learn: Matlab, R, SQL, or Redis
Exposure to geospatial data concepts
Prior use of notebooks or collaborative data environments
Familiarity with Databricks and/or Azure

Benefits

comprehensive health insurance (medical, dental, vision)
employer matching 401(k) retirement plan
paid time off including vacation, holidays, and sick leave
parental leave benefits
tuition reimbursement
professional development support
life and disability insurance coverage
competitive salaries

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythondata analysisdata preprocessingfeature preparationtemporal alignmentresamplinglag featuresspatial associationsanomaly detectionedge-case analysis

Soft Skills

analytical approachwritten communicationverbal communication