1

Fraud Detection Machine Learning Jobs in Baltimore, MD

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

... IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive ... Across private and public sectors-from fraud detection to cancer research to national intelligence ...

... machine learning, and artifi cia l intelligence. In an increasingly connected world, massive ... Across private and public sectors-from fraud detection to cancer research to national intelligence ...

Data Scientist

Edgewood, MD · On-site

$77K - $176K/yr

... IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive ... Across private and public sectors-from fraud detection to cancer research to national intelligence ...

Data Scientist

Edgewood, MD · On-site

$77K - $176K/yr

... IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive ... Across private and public sectors-from fraud detection to cancer research to national intelligence ...

next page

Showing results 1-20

Fraud Detection Machine Learning information

See Baltimore, MD salary details

$10

$17

$26

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

As of Jun 14, 2026, the average hourly pay for fraud detection machine learning in Baltimore, MD is $17.94, according to ZipRecruiter salary data. Most workers in this role earn between $14.81 and $19.09 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 are popular job titles related to Fraud Detection Machine Learning jobs in Baltimore, MD? For Fraud Detection Machine Learning jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Baltimore, MD look for? The top searched job categories for Fraud Detection Machine Learning jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Fraud Detection Machine Learning jobs? Cities near Baltimore, MD with the most Fraud Detection Machine Learning job openings:
Model and Data Manager - Fraud Department - Vice President

Model and Data Manager - Fraud Department - Vice President

Morgan Stanley

Baltimore, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Morgan Stanley rating

8.3

Company rating: 8.3 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

39th of 138 rated financial services


Job description

We are seeking a Fraud Department - Model and Data Manager, Vice President.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Data & Analytics Engineering position at the Vice President level, which is part of the job family responsible for providing specialist data analysis and expertise that drive decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques.

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.

Position Overview

The Model and Data Manager is a key leadership role responsible for the effective onboarding and monitoring of fraud detection and prevention models and data sources. This position will serve as the primary liaison between the Fraud Department and the Model Risk Management (MRM) function, ensuring all fraud models are compliant, robust, and aligned with organizational risk appetite. The VP will drive continuous improvement in model governance and operational excellence. This position reports directly to the Head of Fraud Analytics and Data Science.

What you'll do in the role:

  • Data Onboarding: Working with Fraud Leadership and technology partners, identify and onboard new and ongoing data sources as required to satisfy Fraud data needs to support ongoing Fraud efforts, and enable Fraud coverage of new products and capability launches for the Firm.

  • Model Onboarding: Oversee the end-to-end onboarding process for new internally developed and vendor supplied models, updated fraud models, including coordination with data science, technology, and business teams. Ensure all models meet regulatory and internal standards prior to deployment.

  • Model Monitoring: Lead the ongoing performance monitoring of all fraud models, including periodic validation, back-testing, and performance reporting. Identify model drift, degradation, or emerging risks and coordinate timely remediation.

  • Collaboration with Model Risk Management: Serve as the primary point of contact with the Model Risk Management function. Facilitate model validation, inventory management, control testing, and documentation updates to meet organizational and regulatory requirements. Ensure documentation covers assumptions, limitations, risk controls, data lineage, and governance touchpoints.

  • Governance and Compliance: Govern the end-to-end model life cycle including development, validation, implementation, change management, monitoring, and decommissioning, ensuring robust controls at each stage. Ensure adherence to all internal model governance policies and external regulatory guidelines. Prepare and present model performance and risk assessments to senior management and governance committees.

  • Stakeholder Engagement: Work cross-functionally with fraud operations, analytics, IT, compliance, and audit teams to ensure model integrity, transparency, and accountability.

  • Team Leadership: Lead, mentor, and develop a team of fraud model analysts and specialists. Foster a culture of innovation, collaboration, and continuous learning.

  • Innovation: Assess and guide the adoption of innovative modeling techniques (e.g., AI/ML) within the governance framework. Stay abreast of emerging risks, new fraud typologies, evolving regulatory expectations, and best practices in model risk for financial crimes and fraud detection.

What you'll bring to the role:

  • Bachelor's or Master's degree in quantitative field (e.g., Statistics, Mathematics, Data Science, Engineering, or related discipline).

  • 10+ years of experience in fraud risk management, model risk management, or related analytical functions within the financial services industry.

  • Strong expertise in model development, validation, and governance processes.

  • Demonstrated experience leading cross-functional teams and managing complex projects.

  • Excellent communication, stakeholder management, and presentation skills.

  • In-depth knowledge of regulatory requirements related to model risk (e.g., SR 11-7, OCC 2011-12) is highly desirable.

Preferred Skills

  • Proficiency in data analytics tools and programming languages (e.g., Python, R, PySpark, etc).

  • Demonstrated experience with advanced fraud detection technologies, such as machine learning and artificial intelligence.

  • Ability to manage competing priorities in a fast-paced environment.

What you can expect from Morgan Stanley:


We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Salary range for the position: $135,000 and $190,000 per year. The successful candidate may be eligible for an annual discretionary incentive compensation award. The successful candidate may be eligible to participate in the relevant business unit's incentive compensation plan, which also may include a discretionary bonus component. Morgan Stanley offers a full spectrum of benefits, including Medical, Prescription Drug, Dental, Vision, Health Savings Account, Dependent Day Care Savings Account, Life Insurance, Disability and Other Insurance Plans, Paid Time Off (including Sick Leave consistent with state and local law, Parental Leave and 20 Vacation Days annually), 10 Paid Holidays, 401(k), and Short/Long Term Disability, in addition to other special perks reserved for our employees. Please visit mybenefits.morganstanley.com to learn more about our benefit offerings.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.


What Morgan Stanley employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom