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Fraud Detection Machine Learning Jobs in Lowell, MI

Deloitte

Cyber - SecOps - Consultant

Grand Rapids, MI · On-site

Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response * Working with technologies ...

Deloitte

Cyber Consultant - AI SOC

Grand Rapids, MI

Experience applying artificial intelligence, machine learning, or large language model workflows to ... Assisting with the development, testing, and tuning of detection content aligned to adversary ...

Deloitte

Cyber Manager - AI SOC

Grand Rapids, MI

$106K - $144K/yr

Experience applying artificial intelligence, machine learning, or large language model workflows to ... Overseeing the deployment of log ingestion, normalization, enrichment, routing, detection, and ...

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Fraud Detection Machine Learning information

See Lowell, MI salary details

$10

$16

$25

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

As of Aug 15, 2026, the average hourly pay for fraud detection machine learning in Lowell, MI is $16.82, according to ZipRecruiter salary data. Most workers in this role earn between $13.89 and $17.93 per hour, depending on experience, location, and employer.

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 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 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 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 cities near Lowell, MI are hiring for Fraud Detection Machine Learning jobs?

Cities near Lowell, MI with the most Fraud Detection Machine Learning job openings:

Fraud Detection Machine Learning jobs near you

Cyber - SecOps - Consultant

Deloitte

Grand Rapids, MI • On-site

Full-time

Posted 15 days ago

Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

44th of 150 rated financial services

Job description

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $82,600 - $162,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

If you're looking for an opportunity to work at the intersection of cybersecurity, data, and artificial intelligence, Deloitte's Cyber Defense & Resilience team offers the scale, complexity, and growth environment to build your career. In this role, you will support organizations as they modernize security operations through advanced analytics, cyber data engineering, and AI-enabled capabilities. You will work with leading technologies and help clients strengthen cyber defense while enabling innovation across the enterprise.

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Cyber SecOps Consultant on the Cyber Defense & Resilience team, you will be responsible for...

  • Supporting the design and modernization of cyber data and analytics programs that improve organizational intelligence and enable scalable delivery models
  • Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response
  • Working with technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks to support cyber data platforms and operational outcomes
  • Assisting with the maintenance, enhancement, governance, and administration of data platforms and applications using standardized, automated, and AI-enabled DataOps capabilities
  • Contributing to AI and analytics initiatives by helping clients experiment, operationalize, and scale solutions using cyber and information technology telemetry data

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The team

Cyber Defense & Resilience is an integrated team of security and data technologists working at the intersection of cybersecurity, advanced cyber data engineering, and the use of artificial intelligence and machine learning for cyber defense and operations. The team serves as a trusted advisor and managed service provider, bringing capability and capacity across security data modernization, DataOps, AI, and machine learning to address cyber-specific challenges.

Cyber Detect & Respond practitioners work with clients to modernize large-scale cyber data and analytics programs, support embedded and as-a-service delivery models, and strengthen day-to-day security operations. The team also helps clients harness technologies such as Databricks for Cyber, AWS Security Lake, Google SecOps, Splunk, CrowdStrike, and Palo Alto Networks while advancing AI and analytics capabilities through scalable assets, curated datasets, and operational experience.

Qualifications

Required:

  • 2+ years of analytics consulting or industry experience
  • 2+ years of experience with artificial intelligence development tools, including vector databases such as Pinecone or Elastic, and development frameworks such as LangChain or CrewAI
  • 2+ years of experience in statistical analysis, machine learning, and data mining
  • 2+ years of experience using statistical computer languages such as Python, Structured Query Language (SQL), R, or SAS to prepare data for analysis, perform exploratory analysis, generate features, and support data science workflows
  • 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure
  • 1+ years of experience with security operations center threat hunting and incident response
  • Experience supporting at least one full lifecycle analytics engagement across strategy, design, and implementation
  • Bachelor's degree in Engineering, Mathematics, or Statistics, or 4 years of equivalent professional experience
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • Experience architecting, designing, developing, and deploying enterprise data science solutions that include natural language processing (NLP), chatbots, virtual assistants, computer vision, cognitive services, and big data tools used to manage large datasets
  • Experience applying artificial intelligence (AI), machine learning (ML), and advanced data engineering to cybersecurity use cases, including detection and cyber threat response acceleration
  • Experience parsing and normalizing cybersecurity or information technology telemetry datasets
  • Experience using Python machine learning and deep learning frameworks and libraries, including PyTorch, Keras, TensorFlow, scikit-learn, NumPy, and SciPy
  • Experience designing and implementing Apache open-source frameworks, including Kafka, Storm, and Spark, to support end-to-end data management lifecycle activities
  • Experience managing multiple concurrent task assignments and developing presentation materials using Microsoft Visio and Microsoft PowerPoint

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $82,600 - $162,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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