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Bank Data Analytics Jobs in Portland, OR (NOW HIRING)

Bank is seeking a ServiceNow CMDB Analyst to join our IT Asset Management & Data team. This role is responsible for supporting and improving the Configuration Management Database (CMDB) within the ...

Credit Risk Analyst

Tigard, OR ยท On-site

$90 - $120/hr

Support the maintenance of the Bank's PD and LGD Master Rating Scales.Design and develop risk rating reports and analytical dashboards for various audiences using BI tools with complex and large data ...

Showing results 21-40

Bank Data Analytics information

What is bank data analytics?

Bank data analytics is the process of collecting, processing, and analyzing large volumes of data generated by banking transactions and operations. It helps banks gain insights into customer behavior, detect fraud, manage risks, and improve decision-making. By leveraging advanced analytical tools and techniques, banks can enhance customer experiences, increase efficiency, and develop data-driven strategies for growth. Bank data analytics professionals work with big data, machine learning, and statistical models to extract meaningful patterns and support business objectives.

How does a bank data analytics professional typically collaborate with other departments within a financial institution?

Bank Data Analytics professionals work closely with various departments such as risk management, marketing, compliance, and IT. They translate complex data sets into actionable insights, guiding strategic decisions and helping teams understand customer behavior, detect fraud, and ensure regulatory compliance. Regular cross-functional meetings and project-based collaborations are common, allowing analytics professionals to align data-driven recommendations with business goals and operational needs. This collaborative structure enhances communication, streamlines workflow, and maximizes the value of data across the organization.

What are the key skills and qualifications needed to thrive as a bank data analytics professional, and why are they important?

To thrive as a Bank Data Analytics professional, you need strong analytical skills, proficiency in statistics, and a solid background in finance or economics, often supported by a relevant degree. Expertise in data analysis tools such as SQL, Python, R, and experience with business intelligence platforms like Tableau or Power BI, as well as knowledge of data governance frameworks, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication help translate complex data insights into actionable recommendations for stakeholders. These skills are crucial for driving data-informed decisions that enhance financial performance and risk management in the banking sector.

What is the difference between Bank Data Analytics vs Bank Data Analyst?

AspectBank Data AnalyticsBank Data Analyst
Required SkillsData analysis, statistical modeling, programming (SQL, Python)Data analysis, reporting, basic statistical skills
Work EnvironmentData teams, analytics departments within banksBank branches, finance departments, risk management teams
CertificationsData analytics certifications, SQL, Python coursesFinance or banking certifications, possibly data skills
Industry UsageFocus on developing analytics models and insightsFocus on interpreting data for decision-making

Bank Data Analytics involves advanced data modeling and technical skills to develop insights, while a Bank Data Analyst primarily interprets data to support banking operations. Both roles require analytical skills, but Bank Data Analytics is more technical and model-driven, whereas Bank Data Analyst focuses on reporting and data interpretation within banking environments.

What does a bank data analyst do for a bank?

A bank data analyst collects, processes, and analyzes financial data to identify trends, improve decision-making, and support risk management. They use tools like SQL, Excel, and data visualization software to interpret large datasets and provide insights to enhance banking operations and compliance.

What job categories do people searching Bank Data Analytics jobs in Portland, OR look for?

The top searched job categories for Bank Data Analytics jobs in Portland, OR are:

What cities near Portland, OR are hiring for Bank Data Analytics jobs?

Cities near Portland, OR with the most Bank Data Analytics job openings:

Infographic showing various Bank Data Analytics job openings in Portland, OR as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Head of Data Engineering & Platform

Embedded Shishya

Portland, OR โ€ข On-site

$290 - $362/hr

Other

Posted 22 days ago


Key responsibilities

  • Build, lead, and develop a high-performing team of data and analytics engineers responsible for Mercury's core data infrastructure.

  • Define and execute Mercury's long-term data platform strategy, including architecture, tooling, and reusable data products.

  • Build a platform that makes Mercury's data easy for both people and AI systems to discover, understand, and use, investing in semantic models, metadata, and developer tooling.


Job description

In the early 1970s, Ken Thompson and Dennis Ritchie built Unix around a deceptively simple idea: create small, composable tools that work well together. That philosophy went on to shape modern operating systems, developer tooling, cloud infrastructure, and much of the software we rely on todayโ€”not because any individual tool was revolutionary, but because the platform made everyone else more productive.

We're looking for a Head of Data Engineering & Platform who can build the data platform that gives Mercury that same leverageโ€”creating a foundation where trusted data is easy for both people and AI systems to discover, understand, and work with.

In this role, you'll lead and grow a high-performing team of data engineers responsible for Mercury's core data infrastructure. You'll shape the architecture, tooling, and engineering practices that enable reliable analytics, accelerate product development, and enable the next generation of AI-powered products and internal tools.

* Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

Here are some things youโ€™ll do on the job:
  • Build, lead, and develop a high-performing team of senior data and analytics engineers responsible for Mercury's core data infrastructure, setting a high technical bar and cultivating a strong engineering culture
  • Define and execute Mercury's long-term data platform strategy, building the architecture, tooling, and reusable data products that power analytics, AI, operational systems, and self-service across the company
  • Build a platform that makes Mercury's data easy for both people and AI systems to discover, understand, and use, investing in semantic models, metadata, and developer tooling that make trusted data reusable across the company
  • Establish the foundations for a trusted, resilient data platform by driving best practices for reliability, observability, data quality, governance, privacy, security, and regulatory compliance
  • Partner closely with Engineering, Product, Data Science, Security, and Infrastructure leaders to ensure Mercury's data platform accelerates product development, business operations, and decision-making
You should:
  • Bring 10+ years of relevant experience, including 5+ years leading data or engineering teams
  • Have architected modern data platforms at scale, building the data foundations, semantic layers, metadata, and platform capabilities that power analytics, AI, machine learning, and operational systems
  • Demonstrate the technical judgment and organizational influence to evolve data architecture through periods of rapid growth, balancing long-term, well-governed platform investments with near-term product needs
  • Bring deep expertise in modern data infrastructure, including data modeling, orchestration, streaming, storage systems, metadata, and governance
  • Have experience partnering with Security, Legal, Compliance, and Privacy teams to ensure data platforms meet the privacy, security, and regulatory standards expected of a regulated financial institution

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.

Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidateโ€™s experience, expertise, geographic location, and internal pay equity relative to peers.

Our target new hire base salary ranges for this role are the following:

  • US employees: $289,700-$362,100
  • Canadian employees (any location): CAD $273,800-$342,200

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

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