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Remote Fraud Risk Management Jobs in Chicago, IL

1 point system

Senior Data Scientist

Chicago, IL · Remote

Requirement - Senior Data Scientist Location- Chicago, IL-Remote Contract W2 Updated JD PURPOSE ... risk management analytics, litigation analytics, fraud detection, or safety analytics. • ...

CNA

Risk Control Consultant, Virtual Center

Chicago, IL · On-site +1

$72K - $141K/yr

Under general management direction, works within broad limits of authority requiring a high degree ... Performs remote workplace/work site risk evaluation and remote consultative risk improvement ...

Syntiant

Sr. Manager, Treasury

Itasca, IL · On-site +1

Lead risk management function including analysis and corresponding mitigation of foreign currency ... Fraud Protection. About Syntiant : Founded in 2017 and headquartered in Irvine, Calif., Syntiant ...

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All JobsFraud Risk Management JobsRemote Fraud Risk Management JobsRemote Fraud Risk Management Jobs in Chicago, IL

Remote Fraud Risk Management information

See Chicago, IL salary details

$53.1K

$114.9K

$175.1K

How much do remote fraud risk management jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote fraud risk management in Chicago, IL is $114,919.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,700.00 and $132,900.00 per year, depending on experience, location, and employer.

How does a Remote Fraud Risk Management professional typically collaborate with cross-functional teams to mitigate risks?

Remote Fraud Risk Management professionals regularly work alongside departments such as IT, compliance, customer service, and legal to identify and address potential fraud threats. Collaboration often involves virtual meetings, sharing data insights, and developing joint strategies to detect suspicious activity. Effective communication and the ability to explain complex risk scenarios to non-specialists are crucial. This cross-functional teamwork ensures that fraud prevention measures are integrated throughout the organization and that responses to incidents are swift and coordinated.

What are the key skills and qualifications needed to thrive in Remote Fraud Risk Management, and why are they important?

To thrive in Remote Fraud Risk Management, you need strong analytical skills, attention to detail, and a background in finance, business, or a related field, often supported by relevant certifications such as CFE (Certified Fraud Examiner). Familiarity with fraud detection software, data analysis tools, and case management systems is typically required. Excellent communication, critical thinking, and problem-solving abilities set top performers apart in this role. These skills and qualities are essential for effectively identifying, preventing, and responding to fraudulent activities in a remote environment.

What is the difference between Remote Fraud Risk Management vs Remote Fraud Analyst?

AspectRemote Fraud Risk ManagementRemote Fraud Analyst
CredentialsCertifications in fraud prevention, risk management, or related fieldsBasic knowledge of fraud detection, often with certifications like ACFE or similar
Work EnvironmentStrategic, policy development, and oversight roles within organizationsOperational, investigative roles focused on analyzing transactions and detecting fraud
Employer & Industry UsageFinancial institutions, e-commerce, and fintech companiesBanking, online retail, and payment processing companies
Search & Comparison IntentUnderstanding strategic risk management roles in fraud preventionOperational roles focused on fraud detection and analysis

Remote Fraud Risk Management involves developing policies and overseeing fraud prevention strategies, while Remote Fraud Analysts focus on analyzing transactions to detect and investigate fraud. Both roles are essential in combating fraud but differ in scope and responsibilities.

What is Remote Fraud Risk Management?

Remote Fraud Risk Management refers to the processes and strategies used to detect, prevent, and respond to fraudulent activities in digital environments, especially when employees and operations are distributed or working remotely. This role involves monitoring transactions, analyzing data for suspicious patterns, and implementing security measures to minimize risks. Professionals in this field work closely with IT, compliance, and legal teams to ensure that systems and data remain secure despite the challenges of remote work. Effective remote fraud risk management is critical for protecting organizations from financial losses and reputational damage.
What are the most commonly searched types of Fraud Risk Management jobs in Chicago, IL? The most popular types of Fraud Risk Management jobs in Chicago, IL are:
What are popular job titles related to Remote Fraud Risk Management jobs in Chicago, IL? For Remote Fraud Risk Management jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Fraud Risk Management jobs in Chicago, IL look for? The top searched job categories for Remote Fraud Risk Management jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Fraud Risk Management jobs? Cities near Chicago, IL with the most Remote Fraud Risk Management job openings:
Remote Fraud Risk Management jobs near you
Senior Data Scientist

Senior Data Scientist

1 point system

Chicago, IL • Remote

Contractor

Re-posted 2 days ago

Job description

Requirement - Senior Data Scientist

Location- Chicago, IL-Remote

Contract W2

Updated JD

PURPOSE:
The Sr Data Scientist will design and implement machine learning and NLP solutions for a claims and incident mitigation analytics project. This role will help risk management teams identify high-risk incidents earlier, classify claims by likely severity and financial impact, and provide explainable insights that support faster intervention. The position responsibilities outlined below are not all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.

POSITION RESPONSIBILITIES:
• Translate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classification.
• Profile, clean, and prepare claims and incident data for analytics, modeling, and scoring.
• Develop feature engineering logic using structured and unstructured claims and incident data.
• Apply NLP and text-processing techniques to claim and incident narratives to extract useful risk signals.
• Develop record-linkage approaches to connect incidents and claims when a clean unique identifier is not available.
• Build and validate models that rank incidents by likelihood of becoming claims or requiring Risk Management intervention.
• Build and validate claim severity models that classify claims by likely financial impact and high-dollar claim risk.
• Generate explainability outputs, including key risk drivers and business-readable reasons for flagged incidents or claims.
• Collaborate with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps partners to deliver usable business outputs.
• Monitor model performance, drift, scoring quality, and retraining needs.
• Document modeling assumptions, feature logic, validation results, limitations, and handoff requirements.
• Ensure data science work follows data governance expectations, including appropriate handling of PII and sensitive fields.
• Present findings, model results, and recommendations to business and technical stakeholders in a clear, actionable manner.

EXPERIENCE AND QUALIFICATIONS:

Required Skills -
• Strong experience building supervised machine learning models, especially classification, ranking, and severity / risk scoring models.
• Strong experience with data profiling, data cleaning, feature engineering, model validation, and model evaluation.
• Experience working with messy, sparse, real-world enterprise datasets.
• Strong Python and SQL skills.
• Experience with NLP or text analytics, including narrative cleaning, text classification, embeddings, keyword extraction, or summarization.
• Experience with probabilistic record linkage, entity resolution, fuzzy matching, or deduplication.
• Experience explaining model outputs using feature importance, SHAP, reason codes, or other explainability methods.
• Experience working with Snowflake or similar enterprise data warehouse platforms.
• Experience supporting batch scoring, model monitoring, and production handoff.
• Strong understanding of data governance, sensitive data handling, and PII masking or exclusion.
• Excellent communication and teamwork skills.

PREFERRED SKILLS:
• Experience with insurance claims, risk management analytics, litigation analytics, fraud detection, or safety analytics.
• Experience with claim severity modeling or high-dollar claim prediction.
• Experience with AWS, SageMaker, or similar cloud-based data science environments.
• Experience supporting BI outputs in Tableau, Power BI, Looker, or similar tools.
• Familiarity with MLOps best practices, model versioning, monitoring, and retraining workflows.
• Exposure to hospitality, property operations, guest experience, or enterprise safety data.
• Proven ability to translate complex analytics into practical business workflows and measurable impact.

EDUCATION:
Master's degree in computer science, statistics, data science, industrial engineering, operations research, mathematics, or related field preferred. Bachelor's degree with strong relevant experience acceptable.

5+ years of experience in data science, machine learning, risk analytics, or related area preferred.