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Internship Fraud Data Scientist Jobs (NOW HIRING)

Truist

Card Fraud Data Scientist II

Atlanta, GA

... science solution design, technical delivery, and measurable business outcome. 4. Engage in ... Hands-on expertise with fraud detection tools and data signals , including device intelligence ...

Truist

Card Fraud Data Scientist II

Atlanta, GA · On-site

Experience analyzing fraud trends using large datasets , applying statistical techniques, SQL, and/or data-science tools to identify anomalies, build rules, or evaluate model performance. * Working ...

Truist

Fraud Data Scientist II

Atlanta, GA · On-site

... end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. ...

Truist

Fraud Data Scientist II

Wilson, NC

... end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. ...

Truist

Fraud Data Scientist II

Atlanta, GA · On-site

... end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. ...

Truist

Fraud Data Scientist II

Charlotte, NC · On-site

... end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. ...

Truist

Fraud Data Scientist II

Orlando, FL

... end data science solution design, technical delivery, and measurable business outcome. 4. Engage in stakeholder meetings to identify business objectives and scope solution requirements. 5. ...

Robinhood

Senior Data Scientist, Fraud

Menlo Park, CA · On-site

$187K - $220K/yr

The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat malicious ...

BOK Financial

Data Product Owner - Fraud

Addison, TX

Bonus Type Discretionary Summary The Fraud Data Product Owner is a newly created role at the center ... Science, Data Science, Business or a related field and a minimum of 6 years of experience in ...

BOK Financial

Data Product Owner - Fraud

Addison, TX · On-site

Bonus Type Discretionary Summary The Fraud Data Product Owner is a newly created role at the center ... Science, Data Science, Business or a related field and a minimum of 6 years of experience in ...

BOK Financial

Data Product Owner - Fraud

Tulsa, OK · On-site

The Fraud Data Product Owner is responsible for defining the vision and roadmap for fraud-related ... Required : • Bachelor's Degree in Computer Science, Data Science, Business or a related field • ...

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Internship Fraud Data Scientist information

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How much do internship fraud data scientist jobs pay per year?

As of Jun 24, 2026, the average yearly pay for internship fraud data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Fraud Data Scientist, and why are they important?

To thrive as an Internship Fraud Data Scientist, you need a solid grounding in statistics, data analysis, and machine learning, typically supported by coursework in computer science, mathematics, or a related field. Familiarity with programming languages such as Python or R, data visualization tools, and experience with databases and fraud detection systems are commonly required. Strong problem-solving skills, attention to detail, and effective communication help interns present findings and collaborate with cross-functional teams. These competencies are essential for accurately detecting fraudulent activities and supporting data-driven decisions in a fast-paced business environment.

What does an Internship Fraud Data Scientist do?

An Internship Fraud Data Scientist assists in detecting and preventing fraudulent activities by analyzing large datasets and building predictive models. They work with data related to financial transactions, customer behavior, and patterns of fraud to identify suspicious activities. Interns often use machine learning, statistical analysis, and data visualization tools to support the fraud prevention team. They may also help prepare reports and communicate findings to stakeholders, contributing to the organization's overall risk management strategy.

What kind of projects can an Internship Fraud Data Scientist expect to work on, and how do these contribute to the organization?

As an Internship Fraud Data Scientist, you will likely assist in developing and testing machine learning models aimed at detecting fraudulent transactions or behaviors. Your projects may involve data cleaning, exploratory data analysis, feature engineering, and model evaluation using real-world datasets. These tasks directly contribute to the organization's efforts to minimize financial loss and improve the accuracy of their fraud detection systems. You'll also gain exposure to industry-standard tools and collaborate closely with senior data scientists, risk analysts, and engineering teams, providing valuable learning and networking opportunities.
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Internship Fraud Data Scientist jobs near you

Lead Fraud Data Scientist

Felix Technologies, Inc.

Miami, FL • On-site

Full-time

Medical, Dental, Vision, PTO

This job post has expired today. Applications are no longer accepted.

Job description

About Us
At Félix, we\'re building the financial ecosystem for Latin immigrants in the U.S., starting with a revolution in remittances. Our core product is an AI-powered chatbot built on WhatsApp, allowing our users to send money home as easily as sending a text message. We leverage cutting-edge technology like AI, blockchain, and stablecoins to make cross-border payments faster, more affordable, and more accessible than ever before. 
We are a hyper-growth Series B company, backed by over $100 million in funding from top-tier global investors, including QED, Castle Island, Switch Ventures, HTwenty, Monashees, and General Catalyst Customer Value Fund. This isn\'t just about the numbers; it\'s a testament to the trust our investors have in our vision and our team. Additionally, Félix was selected as an “Endeavour Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award. We are a group of extremely talented and dedicated high-performers, united by our shared obsession with a single goal: empowering our customers. We are all owners of Félix, driven by a bias for action and a true experimentation spirit to get shit done with urgency and focus.
Joining Félix means you will be part of a team building a legacy, a company that will outlive us all. This is a rare opportunity to apply your skills to a deeply meaningful mission—serving a community that has been underserved for too long. We are a team that is fiercely loyal to each other, where radical transparency and constructive feedback are how we grow and push for excellence. We are bold, we care less about what others are doing, and more about creating sustainable value and a product that truly makes our users\' lives better. We are building the future, today.
About the role
As a Lead Data Scientist for our Fraud team, you will be on the front lines of protecting our company and our customers. You will leverage your expertise in machine learning, statistics, and data analysis to design, build, and deploy sophisticated models that detect and prevent fraudulent activity in real-time. This is a high-impact role where you will see your work directly translate into protecting millions of dollars and ensuring a trustworthy platform for our users. 
Responsibilities
  • Technical Leadership & Strategy: Define the long-term machine learning strategy for the fraud team, establish technical best practices, and mentor junior data scientists.
  • End-to-End Model Development: Own the entire lifecycle of fraud detection models, from data exploration and feature engineering to model training, validation, deployment, and monitoring.
  • Credit & Lending Fraud Mitigation: Design and develop models specifically targeted at lending fraud typologies, including synthetic identity fraud, first-party loan default fraud, and application fraud.
  • Advanced Analysis: Conduct deep-dive investigations into emerging fraud patterns and user behavior, using clustering, outlier detection, network analysis, and other unsupervised techniques to uncover hidden risks and organized fraud rings.
  • Experimentation: Design and execute A/B tests to measure the impact of new models, rules, and strategies on both fraud detection rates and user experience.
  • Stakeholder Collaboration: Partner closely with Product, Engineering, Risk, and Operations teams to translate business needs into data science solutions, seamlessly integrate ML scores with rule engines, and communicate complex results to non-technical audiences.
  • Productionalize Models: Deploy, monitor, and maintain machine learning models in a cloud environment, ensuring high availability and performance.
  • Reporting & Visualization: Build and maintain dashboards using tools like Tableau or Looker to track key performance indicators (KPIs) like fraud loss rates, false positive rates, and model performance.

Requirements
Must-Haves:
  • Experience: 5+ years of experience in a hands-on data science role, building and deploying machine learning models.
  • Leadership: Proven experience leading complex data science projects from inception to production, including setting technical direction and guiding peers.
  • Python: Expert-level Python for data analysis and modeling (pandas, scikit-learn, etc.).
  • SQL: Advanced SQL skills for complex data extraction and manipulation.
  • Machine Learning Modeling: Deep experience with tree-based ML models (XGBoost, CatBoost, LightGBM) and statistical models (Logistic Regression, Lasso/Ridge).
  • Model Explainability & Ethics: Deep understanding of model explainability frameworks (SHAP, LIME) and algorithmic fairness to ensure models comply with credit lending regulations.
  • Sampling Techniques: Strong understanding of sampling techniques for handling highly imbalanced datasets.
  • Unsupervised Learning: Practical experience with clustering and outlier detection techniques (e.g., K-Means, K Nearest Neighbors, Isolation Forest).
  • Model Lifecycle & Cloud: Proven experience with the full modeling lifecycle, including model deployment, monitoring, and maintenance on a cloud platform like GCP, AWS, or Azure.
  • Analytical Rigor: A solid foundation in statistics and experience designing and analyzing A/B tests.
  • Communication: Excellent stakeholder management and communication skills, with a demonstrated ability to explain complex technical concepts to diverse audiences. Advanced English level.

Nice to have
  • Domain Experience: Direct experience in a FinTech, payments, or risk/fraud-focused role, particularly with exposure to credit or consumer lending.
  • Alternative & Bureau Data: Experience working with traditional credit bureau data (Experian, Equifax, TransUnion) and alternative credit/identity data sources.
  • Graph ML: Experience with Graph Neural Networks (GNNs) or graph analytics tools (e.g., Neo4j, NetworkX) to map complex fraud networks.
  • Regulatory Familiarity: Familiarity with consumer lending regulations (e.g., FCRA, ECOA) and their impact on machine learning model development.
  • MLOps: Hands-on MLOps experience (e.g., CI/CD for models, versioning, automated retraining).
  • GCP / Vertex AI: Experience with Google Cloud Platform (GCP), especially Vertex AI.
  • Spanish and/or Portuguese speaker

These are the applicable requisites, although equivalent competencies in any of the above will also be considered.
What We Offer
  • Competitive salary
  • Initial stock options grant
  • Annual performance bonus
  • Health, dental, and vision plans 
  • Remote work environment, although we have offices in Miami and México City and would love to work in hybrid model if you are up to it.
  • Continuous learning opportunities 
  • Unlimited PTO
  • Paid parental leave
  • Empowering opportunities for growth in a dynamic entrepreneurial environment

Equal Opportunity Employer
At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.
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