1

Computer Science Finance Jobs in Oregon (NOW HIRING)

OR · On-site

$47K/yr

Teach AP Computer Science Principles, other AP computer science/AI courses as well as possibly teaching AP Personal Finance or other related courses in the Electives Department. Provides rich and ...

OR · On-site

Partner with Product, Engineering, Data Science, Finance, and Operations teams to prioritize and ... Bachelor's degree in Computer Science, Engineering, Mathematics, or related field; advanced degree ...

OR · On-site

Conduct ad hoc analyses to support strategic initiatives Minimum Qualifications * BS/MS in Finance, Economics, Computer Science, Statistics, or related field (or equivalent experience). * 7+ years of ...

Bachelor's degree in Math, Marketing, Statistics, Computer Science, Finance, Economics, Data Science, or a related field * 3-5 years of hands-on experience analyzing eCommerce, digital marketing, and ...

OR · On-site

A degree in Computer Science, finance, or equivalent practical experience. Nice to Have * Hands-on experience with APIs and integrations. You can read API docs, scope integrations, and speak fluently ...

OR · On-site

$300K - $537K/yr

We are a small, focused group of data practitioners who partner with Finance & Strategy, Product ... You have an advanced degree (MS or PhD) in statistics, economics, computer science, mathematics, or ...

OR · On-site

$300K - $537K/yr

We are a small, focused group of data practitioners who partner with Finance & Strategy, Product ... computer science, mathematics, or a related quantitative field, or equivalent applied research ...

Senior Data Engineer II, Finance

OR · Remote

$105K - $143K/yr

Finance data engineering is part of the Data Infrastructure team, working closely with accounting ... Bachelor's degree in Computer Science, computer engineering, electrical engineering or equivalent ...

next page

Showing results 1-20

Computer Science Finance information

What are the key skills and qualifications needed to thrive in Computer Science Finance, and why are they important?

To thrive in Computer Science Finance, you need strong analytical and programming skills, a solid understanding of financial concepts, and typically a degree in computer science, finance, or a related field. Familiarity with financial modeling tools, database management systems, and programming languages like Python, R, or SQL is highly valued, along with certifications such as CFA or FRM. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for collaborating with diverse teams and interpreting complex data. These skills are crucial for developing innovative financial solutions, ensuring data integrity, and driving informed decision-making in the fast-paced finance industry.

What is the difference between Computer Science Finance vs Data Analyst?

AspectComputer Science FinanceData Analyst
Required CredentialsBachelor's in Computer Science, Finance, or related fields; certifications like CFA or FRM beneficialBachelor's in Statistics, Economics, or related fields; certifications like CAP or Microsoft Data Analyst
Work EnvironmentFinancial institutions, tech firms, investment banks; often collaborative and fast-pacedCorporate offices, consulting firms, financial services; data-driven and analytical
Employer & Industry UsageFinance, banking, fintech, tech companiesFinance, marketing, healthcare, consulting

Computer Science Finance professionals combine technical skills with financial knowledge to develop algorithms, models, and software for financial analysis and trading. Data Analysts focus on interpreting data to inform business decisions across various industries. While both roles require analytical skills, Computer Science Finance emphasizes programming and financial expertise, whereas Data Analysts concentrate on data interpretation and reporting.

What is computer science finance?

Computer science finance is an interdisciplinary field that combines principles of computer science with finance. Professionals in this area use technology and programming to analyze financial data, develop trading algorithms, manage risk, and optimize investment strategies. Careers in computer science finance often involve roles such as quantitative analyst, financial software developer, or data scientist for investment firms, banks, or fintech companies. This field requires skills in programming (often Python, R, or C++), data analysis, and a solid understanding of financial markets and instruments.

How does a professional in Computer Science Finance typically collaborate with both technical and financial teams?

Professionals in Computer Science Finance often serve as a bridge between technology and finance departments, translating financial requirements into technical solutions. They might collaborate closely with software engineers to develop financial models or automation tools, and work with analysts or traders to understand market needs and ensure technical solutions align with business goals. Effective communication is key, as they regularly participate in cross-functional meetings, manage project timelines, and provide updates to both technical and non-technical stakeholders. This role requires adaptability and the ability to explain complex concepts in accessible terms.

What Are Finance Jobs for Computer Science Majors?

Finance jobs for computer science majors focus on the analysis of financial data, the development of finance technology (fintech) software and applications to analyze financial markets and automate equities trading, and the creation of algorithms for analysis, fraud detection, and risk management. As a data scientist or quantitative analyst, you perform your duties for an investment firm or bank. If you are a risk management analyst, you work for financial institutions or life insurance companies. A computer science major can also develop software and configure databases for finance businesses or have cybersecurity responsibilities that include protecting data and systems from hackers.

What are popular job titles related to Computer Science Finance jobs in Oregon? For Computer Science Finance jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Computer Science Finance jobs in Oregon look for? The top searched job categories for Computer Science Finance jobs in Oregon are:
Director, Collections Decision Science & Strategy

Director, Collections Decision Science & Strategy

Aqua Finance

Cove, OR • On-site

Full-time

Posted 25 days ago


Job description

The Director, Collections Decision Science & Strategy leads the design, deployment, optimization, and governance of predictive decisioning strategies supporting outbound collections operations across dialer, SMS, email, and digital engagement channels. This role combines advanced analytics, operational strategy, and production decisioning platform ownership to drive recovery performance, customer experience, and regulatory compliance.

This leader is responsible for developing and operationalizing predictive models and decision logic within collections platforms such as Pega Collections, Debt Manager, and dialer orchestration systems. The role partners closely with Operations, Technology, Compliance, and Risk teams to deliver scalable, explainable, and compliant collections strategies aligned with FDCPA, TCPA, CAN-SPAM, Regulation F, UDAAP, and applicable privacy regulations.

Essential Functions

  • Develop, validate, deploy, and optimize predictive models supporting collections segmentation, prioritization, and treatment strategies.

  • Operationalize machine learning and statistical models directly within collections and decisioning platforms, including Pega Collections, Debt Manager, and outbound dialer environments.

  • Translate model outputs into executable decision logic, workflows, thresholds, routing rules, and contact strategies.

  • Monitor production model performance and recalibrate strategies based on drift, operational outcomes, regulatory changes, and portfolio behavior.

  • Design and manage customer segmentation strategies aligned to delinquency stage, risk tiers, roll rates, payment behavior, and customer engagement patterns.

  • Define and govern outbound contact policies, including channel prioritization, cadence strategies, suppression logic, quiet hours, and contact frequency limits.

  • Lead A/B and multivariate testing initiatives across messaging, channel mix, pacing, cadence, and strategy execution.

  • Partner with Dialer Operations and Workforce Management teams to optimize list generation, routing, pacing, penetration rates, and operational efficiency.

  • Develop and maintain executive-level reporting and dashboards measuring RPC, PTP, liquidation rates, cures, roll rates, recovery performance, and operational KPIs.

  • Maintain model governance documentation, change management controls, validation standards, audit readiness, and regulatory compliance support.

  • Collaborate cross-functionally with Compliance, Legal, Technology, Data Engineering, and Operations teams to ensure decision strategies remain compliant, scalable, and operationally effective.

  • Evaluate emerging technologies, decisioning capabilities, and analytics methodologies to continuously improve collections performance and customer outcomes.

Required Education and Experience

  • Bachelor's degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, Finance, Economics, or a related field, or commensurate work experience required

  • 7 years of experience in decision science, collections strategy, credit risk analytics, or predictive modeling within a regulated financial services environment.

  • Hands-on experience developing and deploying predictive models into production decisioning or collections platforms.

  • Experience operationalizing machine learning models such as XGBoost, decision trees, logistic regression, or similar predictive methodologies.

  • Strong SQL skills with working knowledge of Python and/or R.

  • Experience with collections platforms, decision engines, or dialer orchestration tools such as Pega Collections, Debt Manager, Aspect, Genesys, Noble, or similar technologies.

  • Demonstrated experience designing and analyzing A/B testing and champion/challenger strategies in production environments.

  • Strong understanding of FDCPA, TCPA, CAN-SPAM, Regulation F, UDAAP, and applicable privacy regulations impacting collections operations.

  • Experience translating analytical insights into operational strategies and measurable business outcomes.

  • Strong communication and stakeholder management skills with the ability to influence cross-functional teams and executive leadership.

Physical Demands

While performing the duties of this job, the employee is frequently required to sit, stand, walk, visualize, talk, hear, and handle or touch objects or controls. The employee may occasionally lift, push, or pull up to 20 pounds.

This position is an office-based position where you must be able to sit for long periods of time. The employee will be working on a computer 90% of the time.