4,434 Fraud Detection jobs in the United States

Job DescriptionJob Description About DataVisor: DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe. Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us! Position Overview: We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud. Key Responsibilities: Develop and deploy machine learning models for fraud detection and risk assessment. Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data. Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.). Collaborate with engineering and business teams to integrate ML models into production systems. Continuously monitor model performance and refine algorithms to improve accuracy. Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies. Requirements Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus. Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus). Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.). Experience with SQL and data manipulation/analysis in large datasets. Strong problem-solving skills and patience for deep-dive data exploration. Prior or project experience in fraud modeling, risk analysis, or related fields is a plus. Excellent communication skills and ability to work in a collaborative environment. Nice to have Familiarity with big data tools (Spark, Hadoop, Dask). Knowledge of graph-based fraud detection techniques. Experience with cloud platforms (AWS, GCP, Azure). Benefits PTO, Stock Option, Health Benefits #J-18808-Ljbffr

Job DescriptionJob Description

About DataVisor:
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

• Develop and deploy machine learning models for fraud detection and risk assessment.
• Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
• Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
• Collaborate with engineering and business teams to integrate ML models into production systems.
• Continuously monitor model performance and refine algorithms to improve accuracy.
• Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements

• Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus.
• Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
• Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
• Experience with SQL and data manipulation/analysis in large datasets.
• Strong problem-solving skills and patience for deep-dive data exploration.
• Prior or project experience in fraud modeling, risk analysis, or related fields is a plus.
• Excellent communication skills and ability to work in a collaborative environment.

Nice to have

• Familiarity with big data tools (Spark, Hadoop, Dask).
• Knowledge of graph-based fraud detection techniques.
• Experience with cloud platforms (AWS, GCP, Azure).

Benefits

PTO, Stock Option, Health Benefits

About DataVisor:
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

• Develop and deploy machine learning models for fraud detection and risk assessment.
• Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
• Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
• Collaborate with engineering and business teams to integrate ML models into production systems.
• Continuously monitor model performance and refine algorithms to improve accuracy.
• Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus.
• Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
• Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
• Experience with SQL and data manipulation/analysis in large datasets.
• Strong problem-solving skills and patience for deep-dive data exploration.
• Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
• Excellent communication skills and ability to work in a collaborative environment.

• Familiarity with big data tools (Spark, Hadoop, Dask).
• Knowledge of graph-based fraud detection techniques.
• Experience with cloud platforms (AWS, GCP, Azure).

PTO, Stock Option, Health Benefits

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Role Summary/Purpose: The AVP, Fraud Detection, Analysis and Technology is part of the Fraud Detection and Analysis Team tasked to drive fraud mitigation through the detection and related reduction of fraud risks. The AVP will operate fraud technology solutions to assist company fraud teams in identification, investigation, mitigation, and prevention of fraud.

Essential Responsibilities:

• Conduct fraud investigations and detection, with a strong understanding of fraud trends within the financial/card industry, technology systems, analytics, and investigations.
• Manage systems including data storage, operational systems, fraud strategies, and ensure compliance with regulatory requirements.
• Collaborate with cross-functional teams to achieve fraud detection and risk mitigation goals.
• Interact with investigators, analysts, and technology teams to identify fraud and related activities.
• Utilize tools like NEO4J, Linkurious, and execute detective strategies including Cypher coding for queries and analytical rule development.
• Assist in developing and implementing strategies for early fraud detection using advanced analytics and platforms.
• Prepare analytical reports and support investigations by analyzing data from various platforms.
• Identify emerging fraud threats and trends to proactively prevent losses.
• Coordinate with law enforcement and internal teams to establish analytics rules and linkage analysis.
• Review system alerts and intelligence to identify potential fraud threats.
• Perform other duties and special projects as assigned.

Qualifications/Requirements:

• Bachelor's degree with at least 24 months of experience in fraud investigations or 5 years leveraging data and statistical tools in risk functions.
• Minimum of 2 years designing fraud detection strategies or supporting fraud detection processes.
• Experience with SAS, SQL, Python, Cypher, or similar tools for data analysis.

Desired Characteristics:

• Knowledge of fraud detective tools and frameworks like Cypher, Splunk, SPL, Tableau, SIEM.
• Understanding of analytical tools, data warehouses, machine learning, and Graph data science.
• Strong analytical, problem-solving, project management, and communication skills.
• Ability to work in a fast-paced environment and maintain confidentiality.
• Graduate degree in Mathematics, Statistics, or Data Science preferred.

The salary range is $115,000 - $200,000 annually, with eligibility for bonuses based on performance. Actual compensation depends on experience and skill level.

Eligibility Requirements:

• Must be 18 or older, with a high school diploma or equivalent.
• Willing to undergo drug testing, background check, and fingerprinting.
• Legal authorization to work in the U.S. required; no visa sponsorship available.

Our Commitment: We value diversity and inclusion, fostering a culture where all voices are heard and respected.

Reasonable Accommodation: We provide accommodations for qualified individuals with disabilities. Contact our Career Support Line at 1- for assistance.

Job Family Group: Data Analytics

Employment Type: Full-time

Job Function: Finance

Note: The job posting appears active based on provided data, but verify on the official site for current status.

• Conducts thorough reviews and inquiries on identified and suspicious Member accounts within the specified systems
• Completes inbound/outbound calls with members, fraudsters, business entities, or other financial institutions and takes appropriate action based on results
• Analyze and review potentially fraudulent activity, to ensure minimal loss to the organization and SoFi Members
• Coordinates cross-functional communication, to resolve fraud situations and provides recommendations to resolve fraud
• Assist in the development, maintenance, and implementation of SoFi and bank regulatory policies/procedures to detect and prevent fraudulent activity
• Interacts with SoFi members, as needed, who are reporting fraudulent activity
• Review Member accounts for potential fraudulent activity
• Compile information from multiple channels and determine which accounts need to be restricted and what departments need to be contacted
• Enter and maintain accurate case detail notes for all alerts received and report type of fraud on each occurrence
• Provide escalation and updates to the supervisor regarding alerts worked
• Respond promptly and exercise exceptional communication skills to optimize each contact with members, partners, and external vendors/banks
• Ensures compliance with departmental standards and processes to increase production and accommodate work volumes toward enhanced member satisfaction
• Foster a culture of accountability, collaboration, speed, innovation, excellence, and a fun work environment while continuously elevating the quality and caliber of our fiscal controls
• Handle any special projects as assigned by the fraud management team

• 1+ years experience in banking, financial services, and/or other related industries preferred
• Knowledge of personal loan product preferred
• Outstanding time management skills and interpersonal skills, and the ability to work with all levels within the organization in a collaborative manner
• Must be able to establish peer relationships and communicate effectively with multiple company disciplines, cross-functional, and external teams
• Ability to use Microsoft Office products.
• Excellent written and verbal communication skills
• Ability to apply sound judgment, effectively solve problems, and determine fraudulent activity consistently
• Detail-oriented and process-oriented approach
• Accepts responsibility, ownership, and accountability for work results
• Finds a high-volume, dynamic, and team-focused environment engaging
• Ability to organize and prioritize workload
• High school diploma or equivalent required
• Must have the availability to work flexible hours that will include weekends

Data Scientist II - Fraud Prevention and Detection Join to apply for the Data Scientist II - Fraud Prevention and Detection role at Bank of America Data Scientist II - Fraud Prevention and Detection Join to apply for the Data Scientist II - Fraud Prevention and Detection role at Bank of America Get AI-powered advice on this job and more exclusive features. Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Job Description: At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day. Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve. Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations. At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! Job Summary: This job is responsible for performing more complex analysis aimed at improving portfolio risk, profitability, performance forecasting, and operational performance for consumer products and related divisions, such as credit cards. Key responsibilities include applying knowledge of multiple business and technical-related topics and independently driving strategic improvements, large-scale projects, and initiatives. Job expectations include working with business counterparts within the Line of Business and partner organizations including Risk and Product teams. Fraud Prevention and Detection is looking for an energetic and inquisitive experienced data scientist to join our team and help us combat financial crime using graph databases. In this role, you will be expected to work on large and complex data science projects. Collaborating with internal strategy, technology, product, and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses, lowering false positive impacts, improving client experience, and ensuring the Bank minimizes its total cost of fraud. Responsibilities: Link Analysis/Graph analytics to find and mitigate densely connected fraud networks. Developing and tuning graph algorithms to maximize detection of fraud. Work with software developers to create/enhance link analysis process for new fraud detection use cases, and assist with the generation, prioritization, and investigation of fraud rings. Coordinate with stakeholders and tech to deliver process end-to-end, be the gate keeper for issue tracking and remediation. Gather business requirements and translate to technical logic for script development, and design, create and monitor daily report/QA metrics for fraud detection process. Document and prepare attestation response for process and fraud strategy with governance team. Identify, track, and recommend opportunities for process improvement. Coach and mentor peers to improve proficiency in a variety of systems and serve as a subject matter expert on multiple business and technical-related topics. Identify business trends based on economic and portfolio conditions and communicate findings to senior management. Support execution of large-scale projects, such as platform conversions or new project integrations by conducting advanced reporting and drawing analytics-based insights. Required Qualifications: 5+ years of experience in data and analytics is required. Must be proficient with SQL and one of SAS, Python, or Java Critical problem-solving skills including selection of data and deployment of solutions. Proven ability to manage projects, exercise thought leadership and work with limited direction on complex problems to achieve project goals while also leading a broader team. Excellent communication and influencing skills. Thrives in fast-paced and highly dynamic environment. Intellectual curiosity and strong urge to figure out the “whys” of a problem and come up with creative solutions. Model development experience leveraging supervised and unsupervised machine learning (regression, tree-based algorithms, neural networks) Expertise handling and manipulating data across its lifecycle in a variety of formats, sizes, and storage technologies to solve a problem (e.g., structured, semi-structured, unstructured; graph; hadoop; kafka) Desired Qualifications: Advanced Quantitative degree (Masters or PhD) 7+ years of experience; work in financial services is very helpful, with preference to fraud, credit, cybersecurity, or other heavily quantitative areas. Understanding of advanced machine learning methodologies including neural networks, ensemble learning like XGB, and other techniques Proficient with H2O or similar advanced analytical tools Skills: Analytical Thinking Business Analytics Data and Trend Analysis Fraud Management Problem Solving Collaboration Innovative Thinking Monitoring, Surveillance, and Testing Presentation Skills Risk Management Data Visualization Interpret Relevant Laws, Rules, and Regulations Issue Management Oral Communications Written Communications Shift: 1st shift (United States of America) Hours Per Week: 40 Pay Transparency details US - NY - New York - 1114 Avenue Of The Americas - Grace (NY1544) Pay and benefits information Pay range $165,000.00 - $46,200.00 annualized salary, offers to be determined based on experience, education and skill set. Discretionary incentive eligible This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company. Benefits This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Banking Referrals increase your chances of interviewing at Bank of America by 2x Get notified about new Data Scientist jobs in Boston, MA . 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