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Gis Machine Learning Jobs in Oswego, IL (NOW HIRING)

In this role, you will combine geospatial analytics, statistical modeling, machine learning, and ... Experience using GIS platforms such as ESRI ArcGIS, ArcGIS Pro, ArcObjects, or equivalent ...

Sr Data Scientist

Chicago, IL · On-site

$105 - $149/hr

This involves deploying statistical and analytic methods, measurements, and machine learning models ... Knowledge and experience with using GIS tools for spatial data analysis * Experience with ...

Build, validate, and optimize statistical, predictive, and machine learning models using techniques ... GIS applications, and data-driven transportation systems * Apply data management and systems ...

Build, validate, and optimize statistical, predictive, and machine learning models using techniques ... GIS applications, and data-driven transportation systems * Apply data management and systems ...

Build, validate, and optimize statistical, predictive, and machine learning models using techniques ... GIS applications, and data-driven transportation systems * Apply data management and systems ...

Sales Solution Architect

Chicago, IL · Remote

$121K - $173K/yr

Apply GIS, spatial analytics, AI and emerging location technologies to real customer problems ... Exposure to geospatial AI, digital twins, large-scale data or machine-learning solutions. Why HERE?

Research Software Engineer

Chicago, IL · On-site

$110 - $135/hr

... applications, machine learning, and artificial intelligence. This position is eligible for a ... Angular), and/or GIS and spatial data visualization tools; Building AI solutions, including ...

Gis Machine Learning information

See Oswego, IL salary details

$13

$27

$45

How much do gis machine learning jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for gis machine learning in Oswego, IL is $27.13, according to ZipRecruiter salary data. Most workers in this role earn between $20.58 and $32.02 per hour, depending on experience, location, and employer.

What is a GIS Machine Learning job?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are common challenges when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

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

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

What cities near Oswego, IL are hiring for Gis Machine Learning jobs?

Cities near Oswego, IL with the most Gis Machine Learning job openings:

Cyber Threat Defense Sr AI/ML Engineer

Bank of America

Chicago, IL • On-site

$145 - $193/hr

Other

PTO

Posted 6 days ago


Bank Of America rating

8.3

Company rating: 8.3 out of 10

Based on 536 frontline employees who took The Breakroom Quiz

49th of 175 rated banks


Job description

Job Description

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

Job Description

Bank of America's Global Information Security (GIS) team is seeking a Cyber Threat Defense Sr AI/ML Engineer to build and integrate advanced AI and machine learning capabilities into our cyber defense ecosystem. This person will drive innovation across preventative, detective, and responsive security controls by engineering the full spectrum of intelligent automation: deterministic and scripted automation, custom machine learning models, large language models (LLMs), and agentic AI systems. This is a senior individual contributor role balancing hands-on engineering with technical leadership, working closely with leadership and engineering teams to drive AI integration into cyber defense. This engineer will focus on applying AI to defend against modern threats, including threat actors who are themselves leveraging AI, and will partner with security subject matter experts across GIS on defending the bank's own use of AI. The ideal candidate is an experienced AI/ML engineer with deep fundamentals in machine learning theory and practice, strong production engineering discipline, and a working understanding of cybersecurity, who knows that the right solution is sometimes a script, sometimes a model, and sometimes an agent.

Role Responsibilities
  • Design, build, and deploy AI-powered capabilities for threat hunting, anomaly detection, and automated incident response over large-scale security telemetry.
  • Develop and operationalize custom machine learning models and LLM-based workflows tailored to cybersecurity use cases, owning the lifecycle from data preparation and feature engineering through training, evaluation, deployment, and monitoring.
  • Match the technique to the problem: apply deterministic automation, classical machine learning, or generative AI (or a combination) based on the problem structure, the available data, and the operational risk profile.
  • Build LLM-based tooling that multiplies analyst effectiveness, such as investigation support, detection engineering assistance, and knowledge retrieval.
  • Partner with GIS operational and technical teams to identify opportunities for AI-driven enhancements to security controls and architecture.
  • Prototype and evaluate emerging AI technologies for applicability in cyber threat detection and response.
  • Collaborate with offensive security teams to develop AI-enhanced red teaming and adversarial emulation capabilities.
  • Contribute to architectural decisions that support scalable, well-governed AI integration across GIS security controls.
  • Promote responsible and ethical use of AI in security operations, partnering with model governance stakeholders on bias mitigation and explainability.
  • Act as a technical expert on AI-driven cybersecurity initiatives, advising senior leadership and mentoring engineers and analysts.
Required Qualifications
  • 7+ years of hands-on machine learning engineering experience, including fine-tuning, evaluating, and deploying custom models in production.
  • Strong command of machine learning fundamentals, including model training and evaluation (model weights, loss functions, precision, recall, F1, calibration), feature engineering, embeddings, and real-world data issues such as class imbalance, label noise, and model drift.
  • Candidates whose AI experience consists primarily of using generative AI tools, agents, or APIs will not meet this bar; candidates should expect to discuss models they have personally trained and evaluated.
  • Proficiency in Python and hands-on experience with ML frameworks such as PyTorch or scikit-learn, including model evaluation harnesses and experiment tracking.
  • Hands-on experience building LLM-powered applications and agentic AI systems (e.g., retrieval-augmented generation, fine-tuning, tool use, orchestration), grounded in the ML fundamentals above.
  • Experience delivering production systems at scale involving data pipelines, model deployment, MLOps, and automation.
  • Experience with enterprise cloud AI development platforms (e.g., Azure AI Foundry, Amazon Bedrock, Google Cloud Vertex AI) or equivalent open-source or self-hosted model infrastructure.
  • Working understanding of cybersecurity fundamentals (the attack lifecycle, common attacker techniques, and defensive controls) and of how AI can enhance defensive operations.
  • Familiarity with AI governance and model risk management concepts, such as model validation, explainability, and responsible AI.
  • Strong communication and presentation skills, including the ability to translate complex technical concepts for senior executives and cross-functional stakeholders.
  • Bachelor's degree in computer science, a related quantitative field, or equivalent applied experience; advanced degree (MS/PhD) preferred.
Desired Qualifications
  • Experience applying ML or AI to cybersecurity problems such as detection engineering, threat hunting, malware analysis, or security automation.
  • Experience working with security telemetry at scale (e.g., EDR, SIEM, network, or identity data).
  • Understanding of offensive security tactics and threat actor behaviors, and of how AI can enhance red teaming, attack path mapping, and threat modeling.
  • Hands-on offensive security experience (e.g., CTF competitions, red team tooling development, or published security research).
  • Experience with the open-source LLM ecosystem (e.g., Hugging Face, LangChain), LLM guardrails, and agent orchestration frameworks.
  • Familiarity with adversarial machine learning and AI security risks.
  • Experience with AI-enhanced SOAR (Security Orchestration, Automation, and Response) platforms.
  • Prior work in regulated industries, including model risk and compliance considerations in financial services.
Skills
  • Artificial Intelligence
  • Critical Thinking
  • Threat Analysis
  • Cyber Security
  • Data Privacy and Protection
  • Data and Trend Analysis
  • Stakeholder Management
Shift

1st shift (United States of America)

Hours Per Week

40

Pay Transparency details

US - CO - Denver - 1144 15th St - Denver Gis (CO9926), US - DC - Washington - 1800 K St NW - 1800 K Street NW (DC1842), US - IL - Chicago - 540 W Madison St - Bank Of America Plaza (IL4540), US - MA - Boston - 100 Federal St - 100 Federal St Lp (MA5100), US - NJ - Jersey City - 101 Hudson St - 101 Hudson (NJ2101)

Pay and benefits information

Pay range $145,000.00 - $192,500.00 annualized salary, offers to be determined based on experience, education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company.

Benefits

This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.

Privacy Statement

https://careers.bankofamerica.com/en-us/privacy-notice

Pay Transparency

https://careers.bankofamerica.com/en-us/pay-transparency

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About Bank Of America

Sourced by ZipRecruiter

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day. One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

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