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Data Science Jobs in Oregon (NOW HIRING)

Stryker

$35/hr

The data science intern will help drive proactive and predictive insights that inform strategic decision-making across the Commercial Excellence organization within the Trauma & Extremities division.

Stryker

$35/hr

The data science intern will help drive proactive and predictive insights that inform strategic decision-making across the Commercial Excellence organization within the Trauma & Extremities division.

Louisiana State University

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

LSU AgCenter

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

Stryker

$35/hr

The data science intern will help drive proactive and predictive insights that inform strategic decision-making across the Commercial Excellence organization within the Trauma & Extremities division.

Louisiana Workforce Commission

Assistant/Associate Professor (Computational Biology/Data Science) Position Type:Faculty Department:LSUAG PL1 - Department of Plant Pathology and Crop Physiology (Lawrence E Datnoff (00013100)) Work ...

Stryker

$35/hr

The data science intern will help drive proactive and predictive insights that inform strategic decision-making across the Commercial Excellence organization within the Trauma & Extremities division.

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All JobsData Science JobsData Science Jobs in Oregon

Data Science information

See Oregon salary details

$39.6K

$129.8K

$207.8K

How much do data science jobs pay per year?

As of Sep 13, 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 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 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 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 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.

Is a data scientist in high demand?

Data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What jobs can a data scientist do?

A data scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.
More about Data Science jobs

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 job categories do people searching Data Science jobs in Oregon look for?

The top searched job categories for Data Science jobs in Oregon are:

What cities in Oregon are hiring for Data Science jobs?

Cities in Oregon with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Oregon as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 80% Full Time, 15% Part Time, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $129,770 per year, or $62.4 per hour.

Senior Data Scientist - Forecasting

Portland, OR • On-site

Tiger Analytics Inc.
Business Management Consulting • 201 - 500 employees
Learn more about Tiger Analytics Inc.external

Full-time

Re-posted 9 days ago

Job description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking a Senior Data Scientist - Forecasting to join our advanced analytics team supporting leading Retail, CPG, and Supply Chain clients. In this role, you will design, develop, and deploy forecasting solutions that drive critical business decisions across demand planning, inventory optimization, replenishment, logistics, sales forecasting, and supply chain operations.

You will work closely with business stakeholders, data engineers, supply chain planners, and analytics leaders to build scalable forecasting models that deliver measurable business impact. The ideal candidate combines strong statistical forecasting expertise with hands-on machine learning experience and the ability to translate complex analytical findings into actionable business recommendations.

Key Responsibilities

  • Design, develop, and deploy time-series forecasting models including ARIMA, SARIMA, and ETS
  • Build machine-learning-based forecasting models using GBM, Random Forest, XGBoost, and LightGBM
  • Develop hierarchical and multi-level forecasting solutions across products, regions, and channels
  • Perform large-scale data extraction, transformation, and analysis using SQL
  • Partner with supply chain, merchandising, planning, and business teams to understand forecasting requirements.
  • Translate business problems into analytical solutions.
  • Present model insights and recommendations to senior client stakeholders.
  • Lead workshops and forecasting strategy discussions with clients.
  • Implement and operationalize models in cloud environments
  • Collaborate with business stakeholders to translate demand planning requirements into scalable analytics solutions

Requirements

    • 10+ years of experience in applied data science or advanced analytics
    • 5+ years of hands-on experience in demand planning, demand forecasting, or sales forecasting
    • Strong domain experience in CPG, FMCG, retail, or similar industries
    • Advanced proficiency in Python (pandas, NumPy, scikit-learn, statsmodels)
    • Strong SQL skills for large-scale data processing
    • Proven experience deploying models in cloud environments (Azure preferred)

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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