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Machine Learning Geospatial Jobs in North Carolina

Odyssey

Data Scientist I

Charlotte, NC · On-site

Strong proficiency in building advanced machine learning and statistical models using Python, SQL, and modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). * Experience with geospatial ...

Booz Allen Hamilton

Data Scientist

Fayetteville, NC

$99K - $225K/yr

Ever-expanding technologies like IoT, machine learning, and artificial intelligence are generating ... Experience with data visualization or geospatial tools, such as Tableau, Qlik, Power BI, or ArcGIS

Booz Allen Hamilton, Inc.

Data Scientist

Fayetteville, NC · On-site

$99K - $225K/yr

Ever-expanding technologies like IoT, machine learning, and artificial intelligence are generating ... Experience with data visualization or geospatial tools, such as Tableau, Qlik, Power BI, or ArcGIS

Booz Allen Hamilton

Data Scientist

Fayetteville, NC · On-site

$99K - $225K/yr

Ever-expanding technologies like IoT, machine learning, and artifi cia l intelligence are ... Experience with data visualization or geospatial tools, such as Tableau, Qlik, Power BI, or ArcGIS

Booz Allen Hamilton, Inc.

Data Scientist

Fayetteville, NC · On-site

$99K - $225K/yr

Ever-expanding technologies like IoT, machine learning, and artificial intelligence are generating ... Experience with data visualization or geospatial tools, such as Tableau, Qlik, Power BI, or ArcGIS

Booz Allen Hamilton, Inc.

Data Scientist

Fayetteville, NC · On-site

$99K - $225K/yr

Ever-expanding technologies like IoT, machine learning, and artificial intelligence are generating ... Experience with data visualization or geospatial tools, such as Tableau, Qlik, Power BI, or ArcGIS

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All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in North Carolina

Machine Learning Geospatial information

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial specialist, and why are they important?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.
What job categories do people searching Machine Learning Geospatial jobs in North Carolina look for? The top searched job categories for Machine Learning Geospatial jobs in North Carolina are:
What cities in North Carolina are hiring for Machine Learning Geospatial jobs? Cities in North Carolina with the most Machine Learning Geospatial job openings:
Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in North Carolina as of July 2026, with employment types broken down into 2% Locum Tenens, 74% Full Time, 4% Part Time, 4% Contract, 13% Nights, and 3% Summer. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Data Scientist I

Data Scientist I

Odyssey

Charlotte, NC • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

Job description

About Odyssey Logistics
Odyssey Logistics is a global logistics and supply chain partner helping businesses optimize performance through fully integrated, end-to-end solutions. We connect transportation, technology, and expertise across a broad network of services including 3PL and 4PL managed services, multimodal and intermodal transport, warehousing, trucking, Jones Act Ocean, and customs brokerage, ensuring goods move reliably, efficiently, and intelligently around the world.
Today, Odyssey supports more than 6,000 customers globally, delivering scalable, data driven solutions across complex supply chains. What started with a single client has grown into a dynamic, evolving organization focused on performance, precision, and long-term partnership.
What Sets Us Apart:
Our work is complex, fast moving, and highly collaborative. Success here requires people who think strategically, operate with urgency, and navigate across functions to solve real business challenges. We value individuals who take ownership, challenge the status quo, and turn insight into action.
Our culture is grounded in five core values: Win Together, Innovate Boldly, Drive Results, Customer Centric, and Guide with Care. These are not just principles; they shape how we make decisions, partner with customers, and show up for each other.
The Role:
All applicants must be currently authorized to work in the United States. No relocation allowance will be considered unless specifically addressed.
Work Model: Hybrid
Supervisory Responsibilities: Yes
Reports to: Manager, Data Science
Summary: Seeking a highly analytical, innovative, and research-driven Data Scientist to lead the research, design, development, and implementation of advanced artificial intelligence, machine learning, optimization, and geospatial analytics solutions. This role drives end-to-end applied research initiatives, translating cutting-edge modeling approaches into scalable, production-ready systems that solve complex business challenges in logistics and supply chain. The ideal candidate combines deep technical expertise with strong business acumen to provide technical leadership, mentor junior team members, and shape AI-enabled decision-making.
What You'll Do
  • Lead applied research, design, and implementation of advanced AI, machine learning, and spatial-analytics solutions-including Generative AI, predictive modeling, and intelligent automation-to solve complex supply-chain challenges.
  • Drive end-to-end applied research cycles: problem framing, data exploration, feature engineering, rigorous experimentation, validation, and deployment support.
  • Lead rigorous analytical experimentation to evaluate algorithms, compare methodologies, analyze errors, and identify the most effective approaches for operational use cases.
  • Leverage geospatial intelligence and spatial-temporal analysis to support advanced modeling in routing, territory design, network optimization, and service performance improvement.
  • Develop and deploy intelligent AI-powered systems to forecast demand, improve pricing strategies, optimize asset utilization, and enhance overall business efficiency.
  • Establish robust model evaluation, monitoring, and explainability frameworks to ensure algorithms remain accurate, reliable, and responsive to dynamic logistics environments.
  • Translate complex technical research and advanced analyses into clear, actionable business recommendations through dashboards, reports, and stakeholder communication.
  • Provide technical leadership in the architecture of analytical products, collaborating with engineering teams to design internal AI applications, automation tools, and knowledge-based systems.
  • Proactively stay current with advancements in artificial intelligence, deep learning, and optimization, applying state-of-the-art research methods to drive operational excellence.
  • Document methodologies, model architectures, assumptions, and implementation processes to support reproducibility, transparency, and long-term scalability.
  • Provide technical mentorship to junior data scientists, support the hiring and onboarding processes, and contribute to a culture of innovation through team knowledge-sharing and peer reviews.

What You Bring
  • Degree in Data Science, Computer Science, Engineering, Statistics, Artificial Intelligence, or a related quantitative field (PhD preferred).
  • 3+ years of experience applying data science, advanced AI, predictive/prescriptive analytics, and intelligent systems development in enterprise, operational, or supply chain domains.
  • Strong background in deep learning architectures, including experience with neural network-based modeling approaches for forecasting, classification, sequence modeling, and recommendation systems.
  • Experience conducting applied research, experimentation, and model benchmarking, including algorithm comparison, performance evaluation, error analysis, and iterative model improvement.
  • Strong proficiency in building advanced machine learning and statistical models using Python, SQL, and modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
  • Experience with geospatial analytics and spatial data science methods, including working with tools such as PostGIS, QGIS, ArcGIS, or GeoPandas.
  • Hands-on experience with scalable experimentation, feature engineering, and data preparation using large-scale datasets in modern cloud-based environments (e.g., Databricks, AWS, Azure, GCP, MLflow).
  • Demonstrated experience with Generative AI, large language models (LLMs), intelligent automation, and optimization methods (e.g., simulation, forecasting, decision science).
  • Proficient in querying, manipulating, and wrangling complex datasets to support pipeline development. Knowledge of business intelligence tools (e.g., Sigma Computing, Power BI, Tableau) to support visual storytelling, continuous performance monitoring, and business adoption.
  • Deep understanding of model monitoring, explainability, reproducibility, data governance, and responsible AI practices.
  • Strong analytical and communication skills, with a demonstrated ability to convey advanced technical research and methodology to both technical and non-technical stakeholders
  • Proven ability to lead technical initiatives, mentor team members, and work collaboratively in cross-functional teams (research publications or peer-reviewed work is a plus).

Benefits:
We offer a comprehensive and competitive compensation and benefits package, including:
• A choice of medical plans with FSA and HSA options
• Dental Insurance
• Vision Insurance
• Company-paid Life and Disability Insurance
• 401(k) Plan with Company Match
• Paid Time Off (PTO) and Company Holidays
• Employee Assistance Program
• Company Health & Wellness Program
• Discounts with Preferred Vendors
At Odyssey, we believe the best ideas come from people with different skills, experiences, and perspectives. We welcome applicants from all backgrounds and evaluate every candidate based on the qualifications needed for the role, while also valuing the unique strengths, curiosity, and fresh thinking each person brings. Our commitment to inclusion helps fuel innovation and enables us to deliver smarter, more creative solutions for our customers. We are proud to be a workplace where everyone is treated with respect, given equal opportunity to succeed, and encouraged to contribute in meaningful ways. All employment decisions are based on merit, without regard to race or ethnicity, religion, color, sex, gender identity, sexual orientation, age, disability, national origin, veteran status, or any other characteristic protected by federal, state, or local law.
Odyssey does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth and pregnancy-related conditions), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, or any other characteristic protected by applicable federal, state or local laws and ordinances.

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