AI/ML Environmental Data Scientist

CASE Consultants International; Asheville (NC); Hybrid; USD 100,000 - 120,000; Full time

Benefits offered by this job

Company-sponsored healthcare (medical, dental, and vision)

Paid leave

Retirement plan

Training and professional development

Performance-based raises and bonuses

Job summary

CASE Consultants International in Asheville, NC is looking for AI/ML and environmental data professionals to support NOAA Fisheries’ Ecosystem Science Division. The role involves developing workflows for imagery analysis, ecological monitoring, and data processing. Candidates should have a strong background in Python, R, or C/C++, with experience in AI/ML and cloud environments. We offer competitive benefits including healthcare, paid leave, and flexible work options.

Qualifications

• 7+ years experience with Python, R, and/or C/C++.
• Experience developing automated workflows and data pipelines.
• Familiarity with cloud computing environments and virtual machines.

Responsibilities

• Develop and maintain AI/ML workflows for automated imagery analysis.
• Build scalable environmental data-processing pipelines.
• Support cloud-based deployment workflows.

Skills

Python

R

C/C++

AI/ML

Computer Vision

Imagery Analysis

Education

B.S. degree or higher in computer science, data science, computational science, mathematics, statistics, or related field

Tools

Google Cloud Platform

Job description

May 14

Written By Liz Tarquin

Location: La Jolla, CA (hybrid eligible depending on role)

Clearance: Public Trust Eligible. Must be US citizen or authorized to work in the US.

Travel: Not anticipated

Position Overview

CASE is seeking AI/ML and environmental data professionals to support NOAA Fisheries’ Ecosystem Science Division in developing advanced workflows for imagery analysis, ecological monitoring, and automated environmental data processing. This role supports cutting‑edge applications of artificial intelligence, cloud computing, computer vision, and data engineering for large‑scale ecosystem monitoring initiatives involving underwater imagery, animal‑borne sensors, gliders, aerial systems, and remote cameras. Personnel will help operationalize AI/ML‑enabled workflows supporting NOAA’s modernization initiatives and advanced marine ecosystem science programs.

Key Responsibilities

• Develop and maintain AI/ML workflows for automated imagery analysis
• Build scalable environmental data‑processing pipelines
• Support cloud‑based deployment workflows using Google Cloud Platform
• Develop software tools and dashboards using Python and/or C/C++
• Analyze optical imagery and ecological datasets
• Support metadata management, QA/QC, and workflow automation
• Present technical findings and contribute to scientific collaboration efforts
• Support operationalization of NOAA analytical systems and data workflows

Qualifications

• B.S. degree or higher in computer science, data science, computational science, mathematics, statistics, or related field
• 7+ years experience with Python, R, and/or C/C++
• Experience developing automated workflows and data pipelinesExperience with AI/ML, computer vision, or imagery analysis preferred
• Familiarity with cloud computing environments and virtual machines
• Strong analytical, coding, and scientific communication skills

Benefits

Our competitive benefits packages include company-sponsored healthcare (medical, dental, and vision); paid leave; retirement plan; training and professional development; remote and flexible work; performance‑based raises and bonuses; and others.

EEO Statement

CASE is an affirmative action and equal opportunity employer focused on attracting, retaining, and cultivating talented professionals with diverse backgrounds and perspectives and a diverse, inclusive workplace in which our employees thrive. We equitably consider all qualified applicants without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information as per https://www.eeoc.gov/poster.