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Fraud Detection Machine Learning Jobs in Springfield, MO

Bass Pro Shops

Lead Engineer AI/ML - Onsite

Springfield, MO · On-site

$93K - $122K/yr

The Machine Learning Engineer designs, builds, tests, and optimizes machine learning systems that ... detection, multimodal AI, or generative AI. * Experience building production-quality APIs, services ...

Wendy's

Shift Supervisor

Nixa, MO · On-site

$13.25 - $16.75/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Shift Supervisor

Ozark, MO · On-site

$13.50 - $17/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Springfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Shift Supervisor

Springfield, MO

$12.75 - $16/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Springfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Springfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Springfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Ozark, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Shift Supervisor

Marshfield, MO · On-site

$14.50 - $18.50/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Marshfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Shift Supervisor

Bolivar, MO · On-site

$14.25 - $18/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Assistant Manager

Springfield, MO · On-site

... learning from one another. SEEKING FULL TIME ASSISTANT MANAGERS: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

Wendy's

Shift Supervisor

Republic, MO · On-site

$14.25 - $18/hr

... and learning from one another. SEEKING FULL TIME SHIFT SUPERVISOR: With the right attitude ... detect, position. May use a register, slicer, knives, scissors, other machinery, and a computer.

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Springfield, MO

Fraud Detection Machine Learning information

See Springfield, MO salary details

$9

$16

$24

How much do fraud detection machine learning jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for fraud detection machine learning in Springfield, MO is $16.42, according to ZipRecruiter salary data. Most workers in this role earn between $13.56 and $17.50 per hour, depending on experience, location, and employer.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What are some common challenges faced by professionals working in fraud detection machine learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What are the key skills and qualifications needed to thrive as a fraud detection machine learning specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are popular job titles related to Fraud Detection Machine Learning jobs in Springfield, MO?

For Fraud Detection Machine Learning jobs in Springfield, MO, the most frequently searched job titles are:

What job categories do people searching Fraud Detection Machine Learning jobs in Springfield, MO look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Springfield, MO are:

Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in Springfield, MO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $34,155 per year, or $16.4 per hour.

Lead Engineer AI/ML - Onsite

Bass Pro Shops

Springfield, MO • On-site

$93K - $122K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 22 days ago

Bass Pro Shops rating

6.4

Company rating: 6.4 out of 10

Based on 439 frontline employees who took The Breakroom Quiz

17th of 39 rated national retailers

Job description

We are seeking a Machine Learning Engineer to join the Information Technology organization at our corporate office in Springfield, MO.
The Machine Learning Engineer designs, builds, tests, and optimizes machine learning systems that support enterprise AI initiatives across the business. This role is responsible for developing production-ready model code, inference logic, and reusable ML components that convert approved enterprise data into reliable operational signals, recommendations, automations, or insights.
This position works closely with AI leadership, Data Science, MLOps, Data Engineering, Product/Delivery, Security, Privacy, Store Operations, Merchandising, and other cross-functional partners to implement practical AI solutions. The role must balance model quality, latency, cost, privacy, maintainability, and operational usefulness.
This position requires working onsite in our Springfield, MO headquarters. Occasional travel to field locations may be required.
ESSENTIAL FUNCTIONS:
  • Design, develop, and evaluate machine learning models and inference pipelines for enterprise AI use cases across retail, operations, merchandising, customer experience, supply chain, and corporate functions.
  • Build production-quality Python code for model training, evaluation, preprocessing, postprocessing, inference services, and reusable model components.
  • Partner with Data Scientists to define ground truth datasets, labeling requirements, evaluation metrics, confidence thresholds, and acceptable error tradeoffs.
  • Partner with MLOps / Cloud ML Engineering to package, register, deploy, monitor, and optimize models in cloud, edge, or hybrid environments.
  • Evaluate and select model architectures, pretrained models, fine-tuning approaches, and inference strategies appropriate for the business problem and operating environment.
  • Prepare and transform approved structured and unstructured data for model development while following privacy, retention, and acceptable-use constraints.
  • Build or integrate data labeling, sampling, augmentation, and validation workflows needed for model development and evaluation.
  • Optimize inference performance for latency, cost, throughput, reliability, and deployment target.
  • Implement model output schemas and event metadata structures in partnership with Data Engineering and API/application teams.
  • Integrate model outputs with APIs, event streams, dashboards, reports, applications, or other approved enterprise presentation layers.
  • Write automated tests for model code, preprocessing logic, inference services, schema contracts, and regression checks.
  • Troubleshoot model failures caused by data quality, domain shift, operational changes, drift, or degraded source data.
  • Document model assumptions, limitations, dependencies, reproducibility steps, evaluation results, and production readiness criteria.
  • Support responsible AI practices, including PII minimization, privacy-aware design, model explainability where practical, and secure handling of approved enterprise data.
  • Contribute to architecture decision records, model cards, technical runbooks, documentation, and reusable engineering standards.
  • ALL OTHER DUTIES AS ASSIGNED.

EXPERIENCE/QUALIFICATIONS:
Minimum Degree Required: Bachelor's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Computer Engineering, Applied Mathematics, or a related technical field, or equivalent experience.
  • 8+ years of experience in software engineering, machine learning engineering, applied AI engineering, or production ML systems.
  • 5+ years of hands-on experience building, training, fine-tuning, or deploying machine learning models in applied business environments.
  • Strong proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, OpenCV, or equivalent tools.
  • Experience with one or more ML domains such as natural language processing, forecasting, classification, recommendation systems, optimization, anomaly detection, multimodal AI, or generative AI.
  • Experience building production-quality APIs, services, or batch/streaming inference components.
  • Experience with Git, automated testing, code review, containerization, and collaborative engineering practices.
  • Familiarity with model optimization and deployment formats or tooling such as ONNX, TensorRT, OpenVINO, quantization, batching, or similar techniques preferred.
  • Familiarity with Azure Machine Learning, Azure AI services, Databricks, MLflow, or equivalent cloud ML platforms preferred.
  • Familiarity with event-driven architectures, REST APIs, message queues, data lakes, and metadata/event pipelines preferred.
  • Experience with distributed inference, real-time AI systems, high-throughput event processing, or enterprise integration patterns preferred.
  • Experience working with security, privacy, and governance requirements for sensitive operational data preferred.

KNOWLEDGE, SKILLS, AND ABILITY:
  • Strong software engineering fundamentals and ability to build maintainable ML systems beyond notebooks.
  • Strong understanding of the machine learning lifecycle, including data preparation, training, evaluation, deployment, monitoring, and retraining.
  • Strong understanding of model failure modes in real-world environments.
  • Ability to make practical model tradeoffs across accuracy, latency, cost, privacy, reliability, and maintainability.
  • Ability to translate business use cases into technical model requirements without over-scoping the solution.
  • Ability to collaborate effectively with Data Scientists, MLOps Engineers, Data Engineers, platform teams, and business stakeholders.
  • Ability to document model behavior and limitations clearly for both technical and nontechnical audiences.
  • Proficiency with Git-based development workflows and Agile delivery practices.
  • Commitment to responsible and ethical AI development aligned with company standards.

TRAVEL REQUIREMENTS:
Occasional travel, up to 10%, may be required for field observation, technical validation, troubleshooting, or stakeholder workshops.
PHYSICAL REQUIREMENTS:
Regularly completes computer work and sits.
Occasionally walks and stands.
Seldomly or never lifts up to 50lbs.
INDEPENDENT JUDGEMENT:
Performs duties within scope of general company policies, procedures, and objectives. Analyzes problems and performs needs assessments. Uses judgment in adapting broad guidelines to achieve desired result. Regular exercise of independent judgment within accepted practices. Makes recommendations that affect policies, procedures, and practices.
Full Time Benefits Summary:
Enjoy discounts on retail merchandise, our restaurants, world-class resorts and conservation attractions!
  • Medical
  • Dental
  • Vision
  • Health Savings Account
  • Flexible Spending Account
  • Voluntary benefits
  • 401k Retirement Savings
  • Paid holidays
  • Paid vacation
  • Paid sick time
  • Bass Pro Cares Fund
  • And more!

Bass Pro Shops is an equal opportunity employer. Hiring decisions are administered without regard to race, color, creed, religion, sex, pregnancy, sexual orientation, gender identity, age, national origin, ancestry, citizenship status, disability, veteran status, genetic information, or any other basis protected by applicable federal, state or local law.
Reasonable Accommodations
Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.
If you need a reasonable accommodation for any part of the application process, please visit your nearest location or contact us at hrcompliance@basspro.com.
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