Fraud Data Analyst Jobs

Please note this position is fully remote**

2+ years of experience in SQL

2+ years of experience with programming using R or Python

2+ years of experience leading analyses with a track record of business impact

Financial Services / Fintech / Fraud or Identity sector experience strongly preferred

Data literacy - ability to drive insights and link to recommendations and actions

Manages data definitions and data traceability within data repository to improve documentation and coordination.

Provides support to the business and other internal IT organizations regarding data definition standards, architectures, and policies.

Provides support to business users for mining and interpretation of warehoused and operational data.

Plans and performs activities regarding designed data models for systems development.

Resolves metadata and data sourcing problems. Maintains metadata and data dictionaries.

Manages data definitions and data traceability within data repository to improve documentation and coordination.

Provides support to the business and other internal IT organizations regarding data definition standards, architectures, and policies.

Provides support to business users for mining and interpretation of warehoused and operational data.

Plans and performs activities regarding designed data models for systems development.

Resolves metadata and data sourcing problems. Maintains metadata and data dictionaries.

Manages data definitions and data traceability within data repository to improve documentation and coordination.

Provides support to the business and other internal IT organizations regarding data definition standards, architectures, and policies.

Provides support to business users for mining and interpretation of warehoused and operational data.

Plans and performs activities regarding designed data models for systems development.

Resolves metadata and data sourcing problems. Maintains metadata and data dictionaries.

to gain understanding of how PNC may use or disclose your personal information in our hiring practices.

Strong knowledge of and experience with reporting packages (Business Objects, Tableau, etc.), databases (SQL etc.), programming (XML, ETL frameworks)

Knowledge of statistics and experience using statistical packages for analyzing data sets (Excel, SPSS, SAS etc.)

This Position typically reports to Payments Fraud Manager

3+ years experience of work in data or analytical fields

Experience in internet-based risk and fraud mitigation

No additional years of experience

Work with monitoring team to identify fraud events

Analyze data to identify and understand fraud patterns

Analyze & assessing fraud impacts

Proposing rules and/or other countermeasures to address fraud attack

Measuring the effectiveness of prospective fraud rules and documenting rules for governance approval

Collaborate with other EFO, security, technology, and product partners on comprehensive solutions

Produce regular reports and analysis to communicate fraud trends and risks to management

Build foundational scripts using SQL and database skills

Understanding the nuances of Etsy’s payment processing data and the myriad interactions with our financial systems.

Building rich data sources of truth that interweave complex payments data and foundational data from across the Etsy ecosystem

Finding and advocating for outstanding opportunities for Etsy’s growth that move critical metrics

Analyze data related to payments to identify potential fraud indicators

Investigate groups of fraudulent users and efficacy of new signals and detection methods with the aim of enhancing our detection capabilities

Work closely with cross-functional teams of data and ML engineers, analysts, user researchers, product managers and designers

You have a minimum of 4 years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines

You have a deep understanding of numbers, a strong interest in research, and an experienced and mature business sense

You have expert level SQL and intermediate level Python skills

Strong communication and data presentation skills (such as Tableau and / or Data Studio)

Strong knowledge of and experience with reporting packages (Business Objects, Tableau, etc.), databases (SQL etc.), programming (XML, ETL frameworks)

Knowledge of statistics and experience using statistical packages for analyzing data sets (Excel, SPSS, SAS etc.)

This Position typically reports to Payments Fraud Manager

3+ years experience of work in data or analytical fields

Experience in internet-based risk and fraud mitigation

No additional years of experience

Contribute to the growth of the team's capabilities and understanding of fraud through Cyber specific research and learning activities.

4+ years of data analysis experience preferably with focus on fraud prevention and/or cyber

A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)

Experience and understanding of working in either cyber-fraud intelligence collection & analysis or cyber-enabled fraud prevention and detection

Experience working with multiple cross-functional teams to deliver results

Experience in banking and/or fintech industry

Contribute to the growth of the team's capabilities and understanding of fraud through Cyber specific research and learning activities.

4+ years of data analysis experience preferably with focus on fraud prevention and/or cyber

A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)

Experience and understanding of working in either cyber-fraud intelligence collection & analysis or cyber-enabled fraud prevention and detection

Experience working with multiple cross-functional teams to deliver results

Experience in banking and/or fintech industry

Contribute to the growth of the team's capabilities and understanding of fraud through Cyber specific research and learning activities.

4+ years of data analysis experience preferably with focus on fraud prevention and/or cyber

A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)

Experience and understanding of working in either cyber-fraud intelligence collection & analysis or cyber-enabled fraud prevention and detection

Experience working with multiple cross-functional teams to deliver results

Experience in banking and/or fintech industry

Contribute to the growth of the team's capabilities and understanding of fraud through Cyber specific research and learning activities.

4+ years of data analysis experience preferably with focus on fraud prevention and/or cyber

A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)

Experience and understanding of working in either cyber-fraud intelligence collection & analysis or cyber-enabled fraud prevention and detection

Experience working with multiple cross-functional teams to deliver results

Experience in banking and/or fintech industry

Contribute to the growth of the team's capabilities and understanding of fraud through Cyber specific research and learning activities.

4+ years of data analysis experience preferably with focus on fraud prevention and/or cyber

A degree in a quantitative field of study (e.g., Statistics, Finance, Economics, Math, Sciences, Engineering)

Experience and understanding of working in either cyber-fraud intelligence collection & analysis or cyber-enabled fraud prevention and detection

Experience working with multiple cross-functional teams to deliver results

Experience in banking and/or fintech industry

Excellent research and investigative skills.

CFE certification is a plus!

Applies defined procedures to independently investigate, analyze, and resolve queued fraud and financial risk issues.

Transaction Risk roles can be good for this role.

Works with limited instructions on defined risk cases.

Makes outbound calls to customers to validate payments transactions.

Excellent time management and organization skills

Collaborate with the partner management to manage the relationships and work referred to our vendor.

Minimum Qualifications (desired Candidate Experience, Etc.)

Preferred Qualifications (desired Candidate Experience, Etc.)

Manage partnerships with internal fraud and/or risk departments to help manage fraud and or high risk accounts.

Provide ongoing guidance and assist in training to provide education and increase awareness regarding red flags and suspicious claim identifiers.

At least 2 years of experience in financial services or a related field; bank fraud experience preferred

Process documentation and improvement experience preferred

Clearing fraud flags (non-healthcare clients)

Assisting with approvals for enrollment, support, and client success,

Assisting with documenting and reporting fraud cases

Assisting with updating policies and procedures for ACH enrollment

Knowledge of the BSA/AML requirements

3+ years of experience as a Fraud Analyst in the fintech, travel, and/or ecommerce industries

Strong knowledge of current fraud trends and solutions available in the marketplace

Strong analytical know-how, including experience with enterprise-grade tools such as Looker or Amplitude

Effective verbal and written communication, including effective listening and the knowledge of how to present findings and recommendations

Post-secondary education in Business Administration or related major preferred

Knowledge of the BSA/AML requirements

3+ years of experience as a Fraud Analyst in the fintech, travel, and/or ecommerce industries

Strong knowledge of current fraud trends and solutions available in the marketplace

Strong analytical know-how, including experience with enterprise-grade tools such as Looker or Amplitude

Effective verbal and written communication, including effective listening and the knowledge of how to present findings and recommendations

Post-secondary education in Business Administration or related major preferred

• Excellent Analytical skills with an ability to detect unusual patterns from large data

• Interpersonal and relationship skills, to work effectively within the team and across the country operations teams.

Data Science Analytics and Reporting

Risk and fraud detection models

Monitoring operations and industry trends

• Ability to interpret data and organize information