Data Analyst, Senior - Fraud & Risk

OnPoint Community Credit Union; Portland (OR); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Generous vacation package

100% paid employee medical, dental and

Vision premiums covered

401k matching

Tuition reimbursement

Transit/parking passes

Job summary

OnPoint Community Credit Union is seeking a Data Analyst Senior – Fraud & Risk to transform fragmented data into trusted insights that drive fraud detection, risk mitigation, and audit readiness. You will work in an ML-enabled vendor environment with Verafin and other platforms to build data foundations for in-house modeling.

The role emphasizes cross‑functional collaboration, datasets design, governance, and executive reporting to strengthen organizational decision‑making across fraud and risk

Qualifications

• 5 years of experience in data analytics.
• Advanced SQL and experience with large, messy datasets.
• Experience with Databricks or modern cloud data platforms.
• Proven ability to translate analytics into operational and executive insights.
• Strong data quality and governance practices.
• Dashboard and executive reporting experience.
• Python scripting experience (preferred).

Responsibilities

• Design and maintain fraud and risk analytics datasets.
• Build governed pipelines and curated tables.
• Integrate cross-channel fraud and risk views.
• Perform risk data analysis to identify trends and gaps.
• Conduct quantitative assessments of fraud exposure and risk scenarios.
• Collaborate with Fraud Operations to interpret ML outputs.
• Analyze model performance, thresholds, and operational impacts.
• Develop executive dashboards and investigator reports.
• Support audits and regulatory requests with defensible evidence.

Skills

Advanced SQL proficiency

Databricks / Delta Lake

Trend analysis

Data quality & governance

Dashboard & visualization tools

Python scripting

Data engineering fundamentals

Root cause analysis

Stakeholder communication

Cross-functional collaboration

Fraud concepts familiarity

ML-based alerting concepts

Attention to detail

Tools

Databricks

Job description

OnPoint is the largest community owned credit union in Oregon – and we’re growing! Our growth provides great opportunities for you to reach your personal and professional goals. We value enthusiasm, commitment to outstanding performance, and providing opportunities to truly make a difference. If you are looking to join a team of dedicated, collaborative, and passionate individuals, OnPoint is looking for our next Data Analyst Sr. – Fraud & Risk. We invite you to explore and grow your career with us!

JOB SUMMARY:

The Data Analyst Senior – Fraud & Risk will be responsible for transforming fragmented fraud and risk data into trusted, actionable insights that accelerate fraud detection, investigation, recovery, risk mitigation, and audit readiness. This role operates in an ML‑enabled vendor environment, partnering closely with Fraud Operations, Risk, and Technology to extract maximum value from platforms like Verafin while laying the data foundation for future in‑house modeling. The analyst will also perform risk data analysis across fraud patterns, operational controls, exposure trends, and model performance to strengthen organizational decision‑making.

• Design and maintain fraud and risk analytics datasets in Databricks sourced from Verafin, Accelerant, Q2, Fed files, and other operational systems.
• Build governed, repeatable pipelines and curated tables to replace manual Excel/macros processes.
• Integrate cross‑channel fraud and risk views, such as member, account, product, transaction, case, exposure, or control effectiveness.
• Perform risk data analysis to identify trends, gaps, typologies, control failures, and emerging threats.
• Conduct quantitative assessments of fraud exposure, loss forecasting, and risk scenario analysis.
• Partner with Fraud Operations to interpret and operationalize vendor ML outputs, such as risk scores, alerts, typologies.
• Analyze model performance, false‑positive rates, thresholds, and operational impacts on fraud and risk controls.
• Collaborate with first‑ and second‑line risk teams to ensure model outputs align with broader risk strategies.
• Develop executive‑ready dashboards and investigator‑ready reporting with
• Support audit, compliance, and regulatory requests with defensible evidence, through traceable, well‑documented metrics.
• Contribute to fraud and risk data standards, definitions, metadata, and documentation.
• Collaborate with Technology and Architecture on data ingestion and quality improvements.
• Additional projects, responsibilities, or other duties assigned.

KNOWLEDGE, SKILLS & COMPETENCIES:

• Advanced SQL proficiency, including complex joins, window functions, data cleansing, performance tuning.
• Strong proficiency with cloud data platforms, such as Databricks, Delta Lake, and distributed data processing.
• Proven experience with trend analysis, loss/risk modeling, exposure calculations, scenario analysis.
• Deep expertise in data quality and governance, such as data lineage, metric definitions, documentation, and standardization.
• Expert-level knowledge in dashboard and visualization tools, executive reporting, investigator tools, KPI dashboards.
• Knowledge of python/scripting, including data transformation, automation, and analytics (preferred but not required).
• Working knowledge of data engineering fundamentals, including data modeling, pipeline development, ETL/ELT, and building curated datasets.
• Ability to break down complex data issues, identify root causes, and propose actionable solutions.
• Strong ability to convert data into meaningful operational and risk insights that influence decisions.
• Strong written and verbal communication, with the ability to communicate complex technical issues to employees at all levels.
• Ability to collaborate effectively with cross-functional teams, including senior leaders.
• Working knowledge of fraud schemes, typologies, transaction flows, loss drivers, and enterprise risk frameworks.
• Knowledge of ML‑based alerting systems, risk scoring, thresholding, and model performance concepts.
• Strong attention to detail, ensuring accuracy, traceability, and defensibility of analyses and reporting.

MIN QUALIFICATIONS:

• 5 years of experience in data analytics
• Advanced SQL and experience working with large, messy datasets
• Experience with Databricks or modern cloud data platforms
• Proven ability to translate analytics into operational and executive insights

PREFERRED QUALIFICATIONS:

• 8 years of experience in data analytics, preferably in financial services, risk, or fraud
• Strong understanding of fraud concepts (alerts, cases, typologies, losses, recovery)
• Experience working with vendor fraud platforms (e.g., Verafin)
• Familiarity with model outputs, thresholds, and false‑positive tuning
• Experience supporting audits or regulatory exams
• Experience with Python or similar scripting for data transformation

OnPoint employees are rewarded, acknowledged and appreciated! We take care of our Members, and OnPoint takes care of us by offering employees a generous vacation package, incentives, competitive hourly pay, 100% - paid employee medical, dental and vision premiums, Tri-Met / parking passes, 401k matching, tuition reimbursement and more!

At OnPoint, we believe a workplace that reflects the richness of the world fosters a welcoming and empowering environment for everyone. We're committed to equity and inclusion, and consider all qualified applicants embracing every race, religion, color, sex, national origin, age, sexual orientation, gender identity, disability or veteran status, and your unique background.

We encourage you to apply if you're passionate about this opportunity and have the core qualifications. Your unique experiences and skills are what make you a strong candidate. Don’t let imposter syndrome hold you back! Our recruitment process is designed to be inclusive and accessible to all. If you need any accommodation(s) during the application or interview stage, please let us know. We're dedicated to providing what's necessary to ensure a fair and inclusive experience.