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Data Science Jobs in Oregon (NOW HIRING)

Our AI & Data Science team is small, high-impact, and building a modern AI capability from the ground up on Databricks. You'll ship production solutions - from predictive forecasting to AI agents ...

Stay up to date with the latest trends and technologies in data science and machine learning. * Ability to work independently and collaborate as part of a team * Effective written and verbal ...

$114K/yr

The position works closely with junior team members to mentor and guide their work while collaborating with senior team members and data science managers to deliver impactful solutions. Essential ...

Senior Data Scientist

OR · On-site +1

$140K - $190K/yr

Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling. * Cross-Functional ...

OR · On-site

ABOUT THIS POSITION The Data Science focus specializes in extracting insights and solving complex problems using advanced statistical analysis, machine learning, and predictive modeling. Collects ...

OR · On-site

ABOUT THIS POSITION The Data Science focus specializes in extracting insights and solving complex problems using advanced statistical analysis, machine learning, and predictive modeling. Collects ...

Data Scientist

OR · On-site +1

$75K - $140K/yr

Support Data Science Excellence: Participate in peer reviews, knowledge-sharing forums, and data science communities to promote high-quality analytics practices and continuous learning. * Manage ...

OR · On-site

Identify opportunities to evolve analytics into scalable data science solutions * Work within Azure environments (Databricks, Azure Data Factory) * Work with large healthcare and commercial datasets ...

OR · On-site

Our Data Science team helps scale data driven decision making in these areas. We deep dive to identify opportunity areas and inform Netflix's strategy, run AB tests or utilize other causal inference ...

OR · On-site

They will also serve as a Product Manager of the data science and AI model(s), capturing feedback from stakeholders driving a roadmap for the BI Team. This role requires ongoing collaboration with ...

OR · On-site

$113K - $188K/yr

Data Science Consulting Travel Required: Up to 25% Clearance Required: Ability to Obtain Public Trust What You Will Do: * Partner with stakeholders to define and deliver AI/analytics use cases ...

The BlueLabs Data Science Team develops deep expertise and uses data to inform strategic advice to our clients. Our polling work designs, implements, and fields tools that power our analysis and ...

The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, psychology, geography, physics, statistics, and ...

OR · On-site

$372K - $600K/yr

Work closely with data science and engineering stakeholders to act as a strategic thought partner and onboard new workflows. * Design, build, operate, and maintain mathematics and engineering ...

OR

$372K - $600K/yr

Work closely with data science and engineering stakeholders to act as a strategic thought partner and onboard new workflows. Design, build, operate, and maintain mathematics and engineering ...

OR

$480K - $750K/yr

The Member Experience Data Science and Engineering team is at the forefront of driving innovations in Netflix's core product experience within our streaming and new business domains through data. The ...

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Showing results 1-20

Data Science information

See Oregon salary details

$39.6K

$129.8K

$207.8K

How much do data science jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data science in Oregon is $129,770.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,100.00 and $143,800.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
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 jobs in Oregon? For Data Science jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Data Science jobs? Cities in Oregon with the most Data Science job openings:
Infographic showing various Data Science job openings in Oregon as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, 1% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $129,770 per year, or $62.4 per hour.
Data Scientist

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


AmeriLife rating

8.5

Company rating: 8.5 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

87th of 260 rated insurance


Job description

Our Company

Explore how you can contribute at AmeriLife.

For over 50 years, AmeriLife has been a leader in the development, marketing and distribution of annuity, life and health insurance solutions for those planning for and living in retirement.

Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry.

Job Summary

AmeriLife is a national leader in insurance and financial services. Our AI & Data Science team is small, high-impact, and building a modern AI capability from the ground up on Databricks. You'll ship production solutions - from predictive forecasting to AI agents - that directly transform how the business operates across our Health and Wealth verticals.

Job Description

Why This Role Stands Out

  • Databricks-first platform - Lakehouse architecture with Unity Catalog, MLflow, and scalable compute
  • Real AI work - design and deploy AI agents, RAG systems, and LLM-powered solutions in production
  • End-to-end ownership - from problem framing through deployment and monitoring
  • Direct business impact - work with business leaders on high-visibility initiatives
  • Shape the future - influence technical direction, tooling, and best practices on a growing team

What You'll Do

As a Data Scientist on our AI & Data Science team, you will partner with engineering, analytics, and business stakeholders to translate complex problems into scalable, production-ready solutions. Your work will span the full lifecycle - from exploratory analysis through model deployment and ongoing optimization.

Day-to-day, you will design and build predictive models for forecasting and optimization, develop intelligent automation using AI agents and large language models, engineer features and pipelines on the Databricks Lakehouse platform, and evaluate and iterate on both traditional ML and generative AI solutions to ensure they deliver reliable business value.

This role is ideal for someone who thrives at the intersection of rigorous statistical thinking, practical data engineering, and applied AI innovation - and who wants to do that work on a modern platform where their contributions are visible and valued.

Technical Requirements

Statistics & Machine Learning

Required

  • Strong foundation in statistical modeling and ML, with experience selecting appropriate approaches for different business problems
  • Proven experience building and validating time-series forecasting models in production environments
  • Hands-on expertise with ensemble/boosting algorithms (XGBoost, LightGBM) for structured data
  • Experience with A/B testing design, hypothesis testing, and rigorous model evaluation techniques
  • Comfort working with imperfect, real-world datasets - handling missing data, class imbalance, and feature drift

Preferred

  • Unsupervised learning (clustering, anomaly detection), hierarchical/probabilistic forecasting, Bayesian methods, or causal inference
  • Experience optimizing models for business ROI; exposure to reinforcement learning or advanced optimization

Databricks Platform & Data Engineering

Required

  • Strong Python proficiency for data analysis, modeling, and production development
  • Experience with Databricks notebooks, clusters, and workflows for data science and ML
  • Working knowledge of PySpark for large-scale data processing and feature engineering
  • Advanced SQL skills across Lakehouse architectures; experience with MLflow for experiment tracking and model registry
  • Clean, testable code practices with Git-based version control (e.g., Databricks Repos, GitHub)

Preferred

  • Unity Catalog, Delta Lake/Delta Live Tables, medallion architecture patterns
  • Databricks Feature Store, Model Serving, Workflows orchestration, or data quality frameworks
  • Experience designing APIs for model serving; CI/CD for ML workflows
  • Databricks Accreditations: Fundamentals

Cloud & Infrastructure

Required

  • Hands-on cloud platform experience (Azure preferred; AWS/GCP also valued) with Docker containerization
  • Understanding of cloud-native data architectures, distributed processing, and data governance/RBAC

Preferred

  • Azure ecosystem experience (Data Factory, Azure AI Services, Azure OpenAI); MLOps practices and model monitoring
  • Certification: Azure Fundamentals or AWS Cloud Practicioner

Applied AI & Intelligent Automation

Required

  • Hands-on prompt engineering and LLM integration for production use cases
  • Experience building or orchestrating AI agents and multi-step workflows (LangChain, LangGraph, or similar)
  • Ability to evaluate AI outputs systematically and implement guardrails for reliability and safety
  • Strong judgment on when to apply traditional ML vs. generative AI and the trade-offs involved

Preferred

  • Enterprise LLM experience (fine-tuning, evaluation, deployment); RAG architectures with vector databases and semantic search
  • NLP/text analytics; transformer architectures; Databricks Mosaic AI or Foundation Model APIs
  • Structured AI evaluation methods (offline/online testing, human-in-the-loop); computer vision exposure

Experience & Business Impact

Required

  • 3+ years in data science, machine learning, or applied AI roles
  • Proven ability to communicate complex results as clear, actionable insights for technical and non-technical audiences
  • Full production ownership experience - from problem definition through deployment, monitoring, and iteration
  • Experience leading team-level projects with planning, execution, and delivery accountability

Preferred

  • Insurance, financial services, healthcare, or regulated industry experience
  • Track record of influencing technical direction and elevating team practices

Our Tech Stack

  • Data Platform: Databricks (Lakehouse, Unity Catalog, Delta Lake, MLflow, Workflows)
  • Languages: Python, SQL, PySpark
  • AI/ML: LangChain, LangGraph, Azure OpenAI, Hugging Face, scikit-learn, XGBoost
  • Cloud: Microsoft Azure (Data Factory, AI Services, DevOps)
  • Dev Tools: Git, Docker, VS Code / Cursor IDE, CI/CD pipelines

Education & Location

  • Bachelor's or Master's in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative field. Equivalent experience with a strong portfolio also considered.
  • U.S.-based; remote-friendly with potential hybrid arrangements depending on business needs

Compensation

  • Salary Range: $125,000to $135,000

  • Salary offers will varycommensuratewith experience, education, skills, and training

What AmeriLife Offers

A comprehensive benefits package that includes PTO, medical, dental, vision, retirement savings, disability insurance, and life insurance.

Equal Employment Opportunity Statement

We are an Equal Opportunity Employer and value diversity at all levels of the organization. All employment decisions are made without regard to race, color, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender identity or expression, age, national origin, ancestry, disability, genetic information, marital status, veteran or military status, or any other protected characteristic under applicable federal, state, or local law. We are committed to providing an inclusive, equitable, and respectful workplace where all employees can thrive.

Americans with Disabilities Act (ADA) Statement

We are committed to full compliance with the Americans with Disabilities Act (ADA) and all applicable state and local disability laws. Reasonable accommodations are available to qualified applicants and employees with disabilities throughout the application and employment process. Requests for accommodation will be handled confidentially. If you require assistance or accommodation during the application process, please contact us at HR@AmeriLife.com.

Pay Transparency Statement

We are committed to pay transparency and equity, in accordance with applicable federal, state, and local laws. Compensation for this role will be determined based on skills, qualifications, experience, and market factors. Where required by law, the pay range for this position will be disclosed in the job posting or provided upon request. Additional compensation information, such as benefits, bonuses, and commissions, will be provided as required by law. We do not discriminate or retaliate against employees or applicants for inquiring about, discussing, or disclosing their pay or the pay of another employee or applicant, as protected under applicable law. Pay ranges are available upon request.

Background Screening Statement

Employment offers are contingent upon the successful completion of a background screening, which may include employment verification, education verification, criminal history check, and other job-related inquiries, as permitted by law. All screenings are conducted in accordance with applicable federal, state, and local laws, and information collected will be kept confidential. If any adverse decision is made based on the results, applicants will be notified and given an opportunity to respond.