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Temporary Fraud Data Scientist Jobs (NOW HIRING)

Elder Research

Data Scientist

Arlington, VA · On-site

As a Data Scientist, you will support the Internal Revenue Service's mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data ...

Elder Research

Data Scientist

Arlington, VA · On-site

As a Data Scientist, you will support the Internal Revenue Service's mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data ...

Elder Research

Data Scientist

Arlington, VA

As a Data Scientist, you will support the Internal Revenue Services mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data ...

Bill.com

Fraud Strategy Data Scientist

San Jose, CA · On-site

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

P2P

Data Scientist - Fraud Risk

Manhattan, NY · On-site

$120 - $190/hr

Background in identity risk, AML, payments fraud, or compliance analytics * Fluency in AI‑assisted data analysis / data science tooling Things that enable a fulfilling, healthy, and happy ...

BILL

Fraud Strategy Data Scientist

San Jose, CA · On-site +1

$135K/yr

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

BILL

Fraud Strategy Data Scientist

San Jose, CA · On-site

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

Rain

Data Scientist - Fraud Risk

New York, NY · On-site +1

$50K/yr

Background in identity risk, AML, payments fraud, or compliance analytics * Fluency in AI-assisted data analysis / data science tooling Things that enable a fulfilling, healthy, and happy experience ...

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Temporary Fraud Data Scientist information

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

As of Aug 17, 2026, the average yearly pay for temporary fraud data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a temporary fraud data scientist, and why are they important?

To thrive as a Temporary Fraud Data Scientist, you need strong analytical skills, experience with statistical modeling, and a background in data science or a related field, often supported by a relevant degree. Proficiency in programming languages such as Python or R, knowledge of machine learning frameworks, and familiarity with fraud detection systems are typically required. Strong problem-solving abilities, attention to detail, and effective communication help you quickly adapt and collaborate during short-term assignments. These skills are crucial for rapidly identifying fraudulent activities, delivering actionable insights, and ensuring business integrity within limited timelines.

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

AspectTemporary Fraud Data ScientistFraud Data Analyst
CredentialsDegree in Data Science, Statistics, or related field; experience with machine learningDegree in Data Analysis, Statistics, or related; proficiency in data tools
Work EnvironmentProject-based, short-term assignments, often in financial or e-commerce sectorsOngoing role within fraud prevention teams, often in finance or banking
Employer & Industry UsageFinancial institutions, e-commerce, insurance companiesBanking, credit card companies, online retailers

Temporary Fraud Data Scientists focus on developing models and algorithms to detect fraud, often on short-term projects. Fraud Data Analysts analyze data patterns to identify suspicious activity, typically in ongoing roles. Both roles require data analysis skills but differ in scope, tools, and project duration.

What are some common challenges faced by temporary fraud data scientists when joining an existing analytics team?

Temporary Fraud Data Scientists often face challenges such as quickly adapting to existing data infrastructure, understanding proprietary fraud detection models, and getting up to speed on the organization's specific fraud patterns. Because the role is temporary, there is a need to rapidly build relationships with cross-functional teams, such as compliance, IT, and operations, to access necessary data and insights. Effective communication and the ability to learn organizational processes swiftly are key to delivering impactful analyses within a limited timeframe.

What does a temporary fraud data scientist do?

A Temporary Fraud Data Scientist analyzes large datasets to detect and prevent fraudulent activities within a company, usually on a short-term or project-based contract. They use statistical models, machine learning, and data mining techniques to identify suspicious patterns and anomalies. Their work helps organizations minimize financial losses and improve security measures, often collaborating with other teams like IT, risk management, and compliance. Because the position is temporary, they are typically brought in to address urgent needs, such as investigating a recent spike in fraud or implementing new detection systems.

What cities are hiring for Temporary Fraud Data Scientist jobs?

Cities with the most Temporary Fraud Data Scientist job openings:

What are the most commonly searched types of Fraud Data Scientist jobs?

The most popular types of Fraud Data Scientist jobs are:

What states have the most Temporary Fraud Data Scientist jobs?

States with the most job openings for Temporary Fraud Data Scientist jobs include:

Temporary Fraud Data Scientist jobs near you

Data Scientist

Elder Research

Arlington, VA • On-site

Full-time

Re-posted 12 days ago

Job description

Data Scientist
General Information
Requisition # 674
Locations USA-VA-Arlington
Posting Date 03/04/2026
Security Clearance Required - IRS MBI
Remote Type Hybrid
Time Type Full time
Description & Requirements
Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Scientist to join our team in Arlington, VA. This role is a remote role preferably in the Washington DC area.
As a Data Scientist, you will support the Internal Revenue Service's mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data environments. You will work directly with government clients, program managers, and technical teams to understand business and compliance challenges, design analytical approaches, and deliver data-driven solutions that inform enforcement, audit prioritization, and fraud prevention efforts.
In this role, you will develop, test, and deploy predictive and statistical models using structured and unstructured data to identify anomalies, non-compliance risk, and potential fraud within tax records and related datasets. You will contribute across the full data science lifecycle, from problem formulation and data exploration through model validation, deployment, and stakeholder communication.
Responsibilities include but are not limited to:
  • Prior programming experience, preferably in Python or R, including data exploration, feature engineering, model development, and writing modular, reusable, well-documented code within an iterative development process that includes peer review and collaboration
  • Demonstrated experience using Python, SQL, and Databricks for data analysis, modeling, statistical evaluation, and working with Markdown for technical documentation
  • Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data science-driven solutions in support of assessments, gap analyses, and actionable recommendations for IRS stakeholders
  • Design, develop, test, validate, and implement quantitative and qualitative data science solutions and predictive risk models (including audit selection, refund review, and fraud prevention initiatives) that are modular, maintainable, adaptable to evolving government and regulatory requirements, and supported by robustness, sensitivity, and significance testing to ensure defensible and explainable results
  • Apply statistical and machine learning techniques (supervised and unsupervised) to anomaly detection, fraud identification, and non-compliance risk scoring to help prioritize cases based on compliance risk, fraud indicators, and business impact
  • Collaborate with clients, subject matter experts, and cross-functional teams to refine problem statements, requirements, and analytical approaches, while demonstrating the ability to work independently in a collaborative, fast-paced environment
  • Prepare and deliver technical and non-technical briefings, reports, and presentations to audiences with varying levels of analytical sophistication, translating business and compliance needs into technical solutions with strong interpersonal, written, and verbal communication skills

Minimum Qualifications:
  • Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences
  • 2-10+ years of experience in data science, analytics, or a related technical field
  • Experience using version control systems (e.g., Git) and collaborative development practices
  • Strong understanding of relational databases and SQL
  • Comfortable learning new tools, methodologies, and domains, including working outside your comfort zone
  • Strong analytical mindset with a willingness to tackle complex mathematical and statistical challenges
  • Willingness to travel and work on-site at client locations as required by project needs

Preferred Qualifications:
  • Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM)
  • Experience with PySpark, Unity Catalog, and Jobs in Databricks, with familiarity using platforms and tools such as Databricks and AWS
  • Experience with Natural Language Processing (NLP) and text analytics applied to unstructured documents or case notes, as well as graph analytics and network analysis to identify relationships, fraud rings, or interconnected entities
  • Experience with containerization and environment management (e.g., venv, conda)
  • Experience operating in secure or remote government environments, including use of bash and command-line tools

Clearance Requirements:
  • Must currently possess an IRS Public Trust clearance with Full Background Investigation

Physical Requirements:
  • Must be able to remain in a stationary position 50%
  • Needs to occasionally move about inside the office to access file cabinets, office machinery, etc.
  • Frequently communicates with co-workers, management, and customers, which may involve delivering presentations. Must be able to exchange accurate information in these situation

About Elder Research, Inc - People Centered. Data Driven
Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation.
If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.

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