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Environmental Data Science Jobs in Oregon (NOW HIRING)

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Additional Information Work Environment * Full remote flexibility. Working at SOSi All interested ...

Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ... Additional Information Work Environment * Full remote flexibility. Working at SOSi All interested ...

Qualifications • Bachelor's degree in Environmental Science, Biology, Ecology, Natural Resources ... data management systems. • State-specific permitting and regulatory experience, including ...

Master's/PhD or equivalent experience in Data Science, Statistics, Mathematics, Physics, Operations ... NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity ...

We activate science to deliver progress-developing breakthrough solutions that strengthen ... Support data collection, analysis, and submittal of required environmental reports, including Fire ...

We activate science to deliver progress--developing breakthrough solutions that strengthen ... Support data collection, analysis, and submittal of required environmental reports, including Fire ...

We activate science to deliver progress-developing breakthrough solutions that strengthen ... Support data collection, analysis, and submittal of required environmental reports, including Fire ...

Overview Instacart's Marketing Data Science and Analytics team partners across Marketing, Strategic ... If you thrive in a fast-paced environment that still moves like a startup-and you love rolling up ...

... environments, and personally dive into implementation details when needed. This is not a ... support reporting, analytics, applications, data science, and AI-enabled workflows.

... Data Environment (NDE), Enterprise Data Warehouse (EDW), Enterprise Resource Planning (ERP). * ... Bachelor's degree in Math, science, engineering, or related field. EOE/M/F/ Disability/Vet VEVRAA ...

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Environmental Data Science information

See Oregon salary details

$39.6K

$129.8K

$207.8K

How much do environmental data science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for environmental 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 environmental data science?

Environmental Data Science is an interdisciplinary field that uses statistical, computational, and analytical techniques to collect, analyze, and interpret large sets of data related to the environment. Professionals in this field work on issues like climate change, pollution, biodiversity, and natural resource management by extracting meaningful insights from complex environmental datasets. Their work supports decision-making for policy, conservation, and sustainability initiatives. Environmental data scientists often collaborate with ecologists, geographers, and policymakers to address environmental challenges using data-driven approaches.

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

Environmental data scientists often encounter challenges such as incomplete or inconsistent data, varying data formats, and the need to integrate information from multiple sources like sensors, satellites, and field observations. Addressing missing values, data quality issues, and ensuring proper geospatial alignment can be time-consuming but is essential for producing reliable analyses. Collaboration with domain experts and stakeholders is frequently required to interpret findings and ensure that the results are actionable for environmental policy or management decisions.

What are the key skills and qualifications needed to thrive as an environmental data scientist, and why are they important?

To thrive as an Environmental Data Scientist, you need strong quantitative skills, expertise in environmental science, and a relevant degree in data science, statistics, or a related field. Familiarity with data analysis tools such as Python, R, GIS software, and experience with large datasets or machine learning techniques is typical. Exceptional problem-solving abilities, communication skills, and attention to detail set top performers apart in this field. These competencies are crucial for effectively interpreting complex environmental data, informing policy, and driving impactful sustainability initiatives.

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

AspectEnvironmental Data ScienceEnvironmental Data Analyst
Required CredentialsTypically requires a degree in data science, environmental science, or related fields; often includes programming and statistical certificationsUsually requires a degree in environmental science, geography, or related fields; may include basic data analysis certifications
Work EnvironmentResearch labs, data centers, environmental agencies, or consulting firmsEnvironmental agencies, research organizations, or consulting firms
Employer & Industry UsageUsed in environmental research, climate modeling, and policy analysisUsed in environmental monitoring, reporting, and data interpretation

Environmental Data Science focuses on developing models and algorithms to analyze complex environmental data, often requiring advanced programming skills. In contrast, Environmental Data Analysts primarily interpret and visualize environmental data to support decision-making. Both roles are vital but differ in technical depth and scope.

Is environmental data science a good major?

Environmental Data Science is a relevant major for careers involving analyzing environmental data, modeling ecological systems, and supporting sustainability efforts. It typically combines skills in data analysis, programming, and environmental science, preparing graduates for roles in research, consulting, or government agencies.

What does an environmental data scientist do?

An environmental data scientist analyzes environmental data to identify patterns, assess environmental risks, and support decision-making. They use statistical tools, programming languages like Python or R, and GIS software to interpret large datasets related to climate, pollution, and natural resources.

What are the most commonly searched types of Environmental Data Science jobs in Oregon?

The most popular types of Environmental Data Science jobs in Oregon are:

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

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

What cities in Oregon are hiring for Environmental Data Science jobs?

Cities in Oregon with the most Environmental Data Science job openings:

Infographic showing various Environmental Data Science job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 3% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $129,770 per year, or $62.4 per hour.

Senior Data Scientist, Marketing Analytics (Mobile)

Gametime United

OR • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 days ago


Key responsibilities

  • Own the analytical frameworks for tracking mobile marketing effectiveness and support confident decision-making despite measurement noise.

  • Design, maintain, and analyze marketing analytics dashboards to report performance, user quality, payback, and profitability.

  • Conduct granular analysis of campaign, ad set, ad, and creative performance, providing data-driven recommendations and partnering with marketing.


Job description

Data Science at Gametime

Our Marketing Analytics team is a cross-functional group supporting all aspects of Gametime, partnering closely with User Acquisition to optimize mobile campaign performance across channels like Meta, TikTok, Reddit, and other paid platforms. We drive creative and spend efficiency through rigorous experimentation, advanced measurement, and granular channel analysis, and we work to strengthen the connection between platform-reported performance, attribution-based data, and internal customer economics. The team studies mobile cohorts to identify high-value opportunities across leagues, teams, performers, and user segments, with an eye toward maximizing lifetime value and durable growth.

The Opportunity

We're hiring a Senior Data Scientist to help build and scale the analytical frameworks that power mobile marketing at Gametime, from executive-level performance narratives down to campaign, creative, cohort, and audience-level diagnostics.

The ideal candidate has hands-on experience with mobile marketing, paid social platforms, mobile attribution, experimentation, causal measurement, audience management, and financial profitability modeling in a marketplace or consumer mobile setting, and is comfortable moving fluidly between strategic and highly granular work.

We hire based on impact and capability, not just years of experience. We encourage you to apply and your level will be fully determined and agreed in the interview process.

What You'll Do

  • Own the analytical frameworks for tracking mobile marketing effectiveness in a privacy-aware environment, bridging platform-reported data, attribution data, MMP data, and internal truth to support confident decisions despite measurement noise.
  • Own the end-to-end design and maintenance of marketing analytics dashboards in Sigma/Tableau, serving as a trusted source of truth for performance, user quality, payback, and profitability reporting.
  • Conduct granular analysis on campaign, ad set, ad, and creative performance (IPM, CPM, CPI, CAC, ROAS), providing data-driven recommendations and partnering with marketing to spot creative fatigue and winning assets.
  • Analyze mobile user cohorts to understand retention, monetization, payback, and LTV behaviors, identifying efficiency trends across leagues, teams, and acquisition sources to guide budget allocation.
  • Partner with marketing and finance to understand channel incrementality, profitability, and spend efficiency, building financial scenario models to inform where to scale, reduce, or reallocate spend.
  • Design, analyze, and interpret experiments to measure true channel incrementality and marketing lift, including geo-lift, PSA tests, and audience holdouts, translating results into practical recommendations.
  • Own analytical support for retargeting and audience strategy, building and maintaining user lists and improving segmentation to ensure programs drive incremental value rather than capturing organic demand.
  • Analyze how marketplace conditions, event demand, league mix, pricing, and seasonality influence acquisition efficiency, helping distinguish marketing execution shifts from broader marketplace dynamics.
  • Partner with leadership to translate complex analyses into clear recommendations on spend allocation, channel strategy, and growth investment, communicating tradeoffs and risks to support fast decisions.
  • Stay current on the evolving mobile privacy and attribution landscape (Apple ATT, MMP capabilities) to keep data science a competitive advantage in how Gametime measures and scales mobile growth.

What You'll Bring

  • 7+ years of experience in marketing analytics, growth data science, mobile analytics, or a related field; Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, Economics, or a related field.
  • Prior experience at a mobile-first company, with deep understanding of mobile attribution, Apple ATT, MMPs, and privacy-aware measurement solutions.
  • Hands-on experience with Meta, TikTok, Reddit, or similar paid social platforms, analyzing performance at the campaign, creative, and cohort level.
  • Experience evaluating acquisition and retargeting performance through LTV, CAC, ROAS, payback windows, and profitability models.
  • Experience designing and interpreting marketing experiments or causal measurement studies, such as geo-lift tests and audience holdouts.
  • Experience building, managing, or analyzing user lists for paid marketing activation, with a strong grasp of segmentation, suppression logic, and saturation.
  • Strong foundation in statistics, with experience in experimentation, incrementality measurement, cohort analysis, and causal inference.
  • Experience analyzing creative performance and identifying fatigue to improve testing frameworks.
  • Proficiency in Python or R and SQL, along with hands-on experience with BI tools (Tableau, Sigma) and Mobile Measurement Partners (Adjust, AppsFlyer, etc.).
  • Strong communication skills, with the ability to present technical insights and attribution nuances in a way that supports executive decision-making.
  • Preferred: experience with Marketing Mix Modeling (MMM) or incrementality testing, and experience in ticketing, live events, marketplaces, or consumer mobile apps.
  • Preferred: experience working with highly seasonal businesses, event-driven demand, or shifting supply and pricing dynamics.

What We Offer:

  • Flexible PTO
  • Competitive salary & equity package
  • Monthly Gametime credits for any event ($1,200/yr)
  • Medical, dental, & vision insurance
  • Life insurance and disability benefits
  • Diverse Family-forming benefits through Carrot Fertility
  • 401k, HSA, pre-tax savings programs
  • Company off-sites and meet-ups
  • Wellness programs
  • Tenure recognition