ZipRecruiter

Log In

1

Data Scientist Fraud Detection Jobs in Delaware (NOW HIRING)

JP Morgan Chase

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

... fraud modeling applications. Our work centers on building vision and multimodal AI systems ... visual anomaly detection, synthetic data/image generation, and GenAI-enabled workflows-across ...

Techridge, Inc.

AI Product Owner

Wilmington, DE · On-site

Domain expertise in credit-card systems, fraud detection, or personalized customer marketing ... Technical literacy: familiarity with Python, SQL, data visualization, and AI/ML frameworks (e.g ...

New

ClifyX

GenAI Engineer

Wilmington, DE · On-site

... fraud detection, risk modeling, and customer analytics. • Build, fine-tune, and deploy ML models ... data pipelines for training, validation, and real-time inference • Collaborate with risk ...

previous page

Showing results 41-60

All JobsData Scientist Fraud Detection JobsData Scientist Fraud Detection Jobs in Delaware

Data Scientist Fraud Detection information

What does a data scientist in fraud detection do?

A Data Scientist in Fraud Detection analyzes large datasets to identify patterns and anomalies that could indicate fraudulent activities. They use machine learning algorithms, statistical models, and data mining techniques to detect and prevent fraud in areas like banking, insurance, and e-commerce. Their work helps organizations proactively combat fraud by developing predictive models and automated systems that flag suspicious transactions. Additionally, they often collaborate with other departments to refine detection strategies and ensure compliance with regulations.

What are the key skills and qualifications needed to thrive as a data scientist in fraud detection?

To thrive as a Data Scientist in Fraud Detection, you need a strong background in statistics, machine learning, and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with big data tools (e.g., Hadoop, Spark), and knowledge of fraud detection platforms are essential. Strong problem-solving abilities, attention to detail, and effective communication skills set candidates apart in this field. These skills and qualities are crucial for identifying fraudulent activities quickly and accurately, minimizing financial losses, and supporting organizational security.

How does a data scientist in fraud detection typically collaborate with other teams to develop effective solutions?

As a Data Scientist in Fraud Detection, you will regularly collaborate with cross-functional teams such as fraud analysts, software engineers, and product managers. Working closely with fraud analysts helps you understand emerging fraud patterns, while partnering with engineers ensures your models are effectively integrated into real-time systems. You may also coordinate with compliance and legal teams to ensure solutions meet regulatory requirements. This collaborative approach not only improves the accuracy and impact of fraud detection models but also fosters a dynamic, supportive work environment.

What is the difference between Data Scientist Fraud Detection vs Data Analyst Fraud Detection?

AspectData Scientist Fraud DetectionData Analyst Fraud Detection
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL
Work EnvironmentDeveloping models, advanced analytics, machine learning tasksData cleaning, reporting, basic analysis
Employer & Industry UsageFinancial institutions, e-commerce, insurance

Data Scientist Fraud Detection focuses on building predictive models and applying machine learning techniques to identify fraud patterns. Data Analysts Fraud Detection primarily perform data cleaning, reporting, and basic analysis to support fraud detection efforts. While both roles work in similar industries, Data Scientists handle more complex modeling, whereas Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Data Scientist Fraud Detection jobs in Delaware?

For Data Scientist Fraud Detection jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Data Scientist Fraud Detection jobs in Delaware look for?

The top searched job categories for Data Scientist Fraud Detection jobs in Delaware are:

What cities in Delaware are hiring for Data Scientist Fraud Detection jobs?

Cities in Delaware with the most Data Scientist Fraud Detection job openings:

Data Scientist Fraud Detection jobs near you

CCB Risk Program Associate

JPMorgan Chase & Co.

Wilmington, DE • On-site

$135K - $165K/yr

Full-time

Medical, Retirement

Re-posted 22 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

78th of 175 rated banks

Job description


The CCB Risk Modeling team is seeking talented professionals with expertise in computer vision, Generative AI, and image generation, with a focus on fraud modeling applications. Our work centers on building vision and multimodal AI systems-including image understanding, visual anomaly detection, synthetic data/image generation, and GenAI-enabled workflows-across modern ML platforms and emerging agentic patterns. The ideal candidate will drive these initiatives across model development, evaluation and monitoring tooling, and cross-functional collaboration, ensuring AI/ML solutions are robust, scalable, and aligned with governance, risk, and regulatory expectations.
Key Responsibilities
  1. Model Development: Design and develop machine learning models to drive impactful fraud modeling, covering the entire customer lifecycle, including acquisition, account management, transaction authorization, and collections.
  2. Advanced Machine Learning Techniques: Apply state-of-the-art machine learning methodologies - including deep learning architecture, transformer-based models, and LLMs - on big data platforms to tackle complex business challenges.
  3. Strategic Collaboration: Work closely with senior management to develop and implement ambitious, innovative modeling solutions, ensuring their successful deployment into production environments.
  4. Cross-Functional Partnership: Collaborate with diverse teams, including risk, technology, model governance, and research, throughout the entire modeling lifecycle-from development and review to deployment and operational use.

Basic Qualifications
  1. Ph.D. or Master's degree from a reputable institution in a quantitative discipline such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
  2. 5+ years' experience in creating predictive models, and generative AI solutions using LLM prompt engineering.
  3. Hands-on experience with LLM APIs, Python libraries like Pandas, NumPy, scikit-learn, and others for data manipulation, modeling and analysis.
  4. In-depth knowledge of advanced machine learning algorithms, including logistic regression, XGBoost, Deep Neural Networks (CNN and RNN), clustering, and recommendation systems, with expertise in model design, hyperparameter tuning, and responsible deployment practices.
  5. Demonstrated experience in model interpretability and explainability for complex models such as XGBoost and GBM; experience extending these methods to deep learning architectures (CNNs, RNNs, transformers) is a strong plus.
  6. Familiarity with large language models (LLMs) and their applications, including experience in fine-tuning, prompt engineering, and responsible deployment with appropriate safeguards, monitoring, and auditability.
  7. Proficiency in Python, TensorFlow, PyTorch, Spark, or Scala, coupled with experience in big data technologies such as Hadoop, AWS, and Hive, and familiarity with MLOps tooling that supports model monitoring, drift detection, and end-to-end auditability.

Preferred Qualifications
  1. Strong expertise, interest, and track record of performing cutting-edge research on Gen-AI
  2. Proven track record in designing, building, and deploying high-quality machine learning models in production environments, demonstrating a strong ability to translate theoretical concepts into practical applications.
  3. Demonstrated expertise in data wrangling and model building on a distributed Cloud computation environment (with stability, scalability and efficiency). GPU experience is desired.
  4. Strong ownership and execution; proven experience in implementing models in production.

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
We are here to help you manage your money with checking, savings and credit cards, combining the latest banking technology with comprehensive solutions to meet the financial needs of nearly half of U.S. households.

What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply