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Internship Data Science Economics Jobs in Oregon

Overview This is a general posting for multiple Senior Data Science roles open across our 4-sided ... MS/PhD in Statistics, Economics, Applied Mathematics, or a related field. Currently Opened Roles ...

... experience, internship experience and / or schoolwork/classes/research. The preferred ... Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics. Performing yield ...

We are looking for a Staff Data Scientist to help set the strategic direction for XP, elevate the ... Qualifications Advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied ...

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 ...

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Internship Data Science Economics information

What is an internship in data science economics?

An Internship in Data Science Economics is a temporary position that allows students or recent graduates to gain practical experience applying data science techniques to economic problems. Interns typically work on projects involving data analysis, statistical modeling, and economic research, often using programming languages like Python or R. The role helps bridge the gap between academic knowledge and real-world applications, providing valuable skills for a future career in data science or economics.

What types of projects do interns typically work on in a data science economics internship?

Interns in Data Science Economics roles often work on projects involving data analysis, economic modeling, and statistical research to support business decision-making. These projects may include analyzing large datasets to identify economic trends, building predictive models, and creating visualizations to communicate insights. Interns usually collaborate closely with both data scientists and economists, gaining exposure to real-world applications of economic theories and data-driven problem-solving. This hands-on experience helps interns develop technical and analytical skills while contributing meaningful work to the team.

What are the key skills and qualifications needed to thrive as an internship data science economics, and why are they important?

To thrive as an Internship Data Science Economics, you need a solid background in statistics, econometrics, and programming languages like Python or R, typically supported by progress toward a degree in economics, data science, or a related field. Familiarity with data analysis tools such as SQL, statistical software, and visualization platforms like Tableau is often required. Strong analytical thinking, effective communication, and the ability to collaborate in team environments help interns excel in this role. These skills are crucial for interpreting economic data, delivering actionable insights, and supporting informed decision-making within organizations.

What is the difference between Internship Data Science Economics vs Data Analyst Intern?

AspectInternship Data Science EconomicsData Analyst Intern
Required SkillsStatistics, economics, programming (Python/R), data analysisData analysis, Excel, SQL, visualization tools
Work EnvironmentResearch-focused, economic modeling, data interpretationBusiness insights, reporting, dashboard creation
Industry UsageFinance, consulting, government, research institutionsMarketing, finance, tech companies

Internship Data Science Economics typically involves economic modeling, statistical analysis, and programming skills, often in research or policy environments. Data Analyst Internships focus on interpreting data to generate business insights, using tools like Excel and SQL. Both roles require analytical skills but differ in focus and industry applications.

What are popular job titles related to Internship Data Science Economics jobs in Oregon?

For Internship Data Science Economics jobs in Oregon, the most frequently searched job titles are:

Senior Data Scientist, Marketing Analytics (Mobile)

Gametime United

OR • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


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