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Data Science Associate Jobs in Oregon (NOW HIRING)

Pwc

Data Engineer - Senior Associate

Portland, OR · On-site

$77K - $202K/yr

... and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering ... Data Engineer Associate] is a plus - Designing and implementing thorough data architecture ...

Deloitte

AI Solutions Architect

Portland, OR · On-site

$66.75 - $88/hr

... Azure Data Scientist Associate, or Microsoft Azure Solutions Architect Expert The wage range for this role takes into account the wide range of factors that are considered in making compensation ...

Spyre Therapeutics

OR

$175K - $190K/yr

The Associate Director, Analytical Sciences and Attribute Characterization, oversees structural and ... reports, and data packages, and verification of analytical results to support regulatory ...

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Data Science Associate information

See Oregon salary details

$60.8K

$71.9K

$136.4K

How much do data science associate jobs pay per year?

As of Jun 18, 2026, the average yearly pay for data science associate in Oregon is $71,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,400.00 and $62,900.00 per year, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is 40 too late for data science?

Data Science Associates and other data science roles do not have an age limit; individuals can enter the field at any age. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, which can be learned through online courses, bootcamps, or formal education. Many professionals transition into data science later in their careers and find opportunities based on their experience and skill development.

What can you do with an associate in data science?

A Data Science Associate can analyze data, develop models, and generate insights to support decision-making within organizations. They often work with tools like Python, R, and SQL, and may assist in data cleaning, visualization, and reporting. This role typically requires foundational knowledge of statistics and machine learning techniques.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What are the key skills and qualifications needed to thrive as a Data Science Associate, and why are they important?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What is the work of an associate data scientist?

An associate data scientist analyzes data to identify trends and patterns, develops models using programming languages like Python or R, and supports data-driven decision-making. They often work under supervision to clean data, build algorithms, and communicate findings to teams.

Which is better, DS or CS?

For a Data Science Associate role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes programming, algorithms, and software development. The choice depends on the specific job requirements and your career goals, but proficiency in programming languages like Python or R and understanding of data tools are essential in both fields.
What are the most commonly searched types of Data Science jobs in Oregon? The most popular types of Data Science jobs in Oregon are:
What are popular job titles related to Data Science Associate jobs in Oregon? For Data Science Associate jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Oregon look for? The top searched job categories for Data Science Associate jobs in Oregon are:
Data Science Associate jobs near you
Senior Associate, Underwriting Rules Automation

Senior Associate, Underwriting Rules Automation

New York Life

Remote

$81K - $123K/yr

Other

Posted 20 days ago

Job description

Location Designation: Hybrid - 1 day per quarter 

Role Overview: 

Designs, tests, and governs rules for New York Life's automated underwriting engine, translating underwriting, medical, and actuarial guidance into executable logic that supports straight-through processing.

Requires strong underwriting judgment and comfort with rules platforms, partners across actuarial, data science, technology, medical, and product teams.

What You'll Do: 

Rules Design & Authoring

  • Design and author underwriting rules across key mortality and morbidity risk categories and non-medical factors (build, lifestyle, financial).
  • Convert guidelines and underwriting into structured decision logic in the BRMS and underwriting workbench.
  • Build decision trees using available data (Rx, EHR, MIB, ICD-10, labs, third-party scores) for consistent, auditable outcomes.
  • Define multi-impairment and co-morbidity rules aligned to company and reinsurance standards.
  • Define triage and escalation paths (auto-approve, rate, decline, refer, order requirements).

Rules Governance & Quality Assurance

  • Maintain documentation (rationale, logic narrative, data dependencies, versions, clinical/actuarial basis).
  • Create and execute test cases (standard and edge) and support UAT before deployment.
  • Monitor rule performance (STP, QC, mortality/morbidity) to detect gaps and unintended outcomes.
  • Manage change lifecycle (intake, impact, review, approval, release, post-deploy validation).
  • Ensure rule design meets MRM standards, regulatory requirements, and privacy/fairness guidance.

Cross-Functional Collaboration

  • Partner with actuarial/data science to incorporate model outputs into rule logic (thresholds, overrides).
  • Act as underwriting SME for technology delivery (requirements, review, validation).
  • Work with medical directors and senior underwriters to apply evidence and reinsurer guidance.
  • Identify segments suitable for more automation and support STP improvement priorities.

Continuous Improvement

  • Track emerging evidence and benchmarking to recommend rule enhancements.
  • Engage in reinsurer/industry forums to stay current on best practices and data sources.
  • Develop training and reference materials to support adoption of automated underwriting.

What You'll Bring: 

  • 5+ years individual life underwriting experience with broad medical risk assessment expertise.
  • Strong mortality/morbidity knowledge; familiarity with reinsurer manuals (e.g., Munich Re, RGA, Gen Re, SCOR).
  • Experience with accelerated/automated underwriting and rules-based decision engines.
  • BRMS experience (e.g., Corticon, Blaze, Drools, Pega) building decision tables/trees/flows.
  • Analytical: break down complex histories into clear, auditable decision pathways.
  • Strong writing skills for requirements, rule specs, and test narratives for technical and business audiences.
  • Collaborative, able to work across underwriting, actuarial, data science, technology, compliance, and product.

  Preferred Qualifications

  • Experience integrating third-party data into rules (Rx, EHR, MIB/MVR, financial data, wearables).
  • Exposure to predictive model scores and how to operationalize them in rules.
  • Working knowledge of ICD-10 and clinical terminology used in underwriting.
  • Underwriting experience in LTC, IDI, or critical illness a plus.
  • Familiarity with analytics tools (SQL, Excel, Tableau, Python) for monitoring rule performance.
  • Experience in an MRM framework (documentation and validation for automated decisions).

What We Offer

  • High-impact role accelerating automated underwriting and faster decisions for customers and field.
  • Work at the intersection of underwriting, data science, and technology.
  • Competitive compensation and comprehensive benefits.
  • Support for professional development and relevant designations.
  • Hybrid/remote flexibility and a culture that values balance and performance

#LI - EM1

#LI - REMOTE

Pay Transparency

Salary Range: $81,000-$123,000 

Overtime eligible: Exempt 

Discretionary bonus eligible: Yes 

Sales bonus eligible: No 

Actual base salary will be determined based on several factors but not limited to individual's experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.

Company Overview 

At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact. 

Our diverse business portfolio creates opportunities to make a difference across industries and communities-inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you'll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress. 

As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what's next, and your growth powers it. 

Our Benefits

We provide a full package of benefits for employees - and have unique offerings for a modern workforce, including leave programs, adoption assistance, and student loan repayment programs. Based on feedback from our employees, we continue to refine and add benefits to our offering, so that you can flourish both inside and outside of work. Click here to discover more about our comprehensive benefit options or visit our NYL Benefits Site.

Our Commitment to Inclusion

At New York Life, fostering an inclusive workplace is fundamental to who we are and how we serve our communities. We have a longstanding commitment to creating an environment where individuals can contribute their best and succeed together. This foundation is rooted in our core values of humanity and integrity, ensuring that every employee feels valued and supported. By embracing a broad range of perspectives and experiences, we achieve greater success and fulfill our promise of providing financial security and peace of mind to families across all communities. Click here to learn more about New York Life's leadership in this space.

Recognized as one of Fortune's World's Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We're proud that due to our mutuality, we operate in the best interests of our policy owners. To learn more about career opportunities at New York Life, please visit the Careers page of www.NewYorkLife.com.

Visit our LinkedIn to see how our employees and agents are leading the industry and impacting communities.

Visit our Newsroom to learn more about how our company is constantly evolving to meet our clients' and employees' needs.

Job Requisition ID: 93678

NorCal Orange logo

About NorCal Orange

Sourced by ZipRecruiter

Industry

Colleges, universities, and professional schools

Company size

11 - 50 Employees

Headquarters location

Syracuse, NY, US

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