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Summer Causal Inference Jobs (NOW HIRING)

Smadex SLU

Senior Product Manager

New York, NY · On-site

$138K - $182K/yr

This is a builder role for someone who is comfortable reasoning about causal inference ... Summer Fridays & Team building events Powered by JazzHR YOLpoBk9wz

Stripe

PhD Data Scientist, Intern

San Francisco, CA · On-site

Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure ... or spring/summer 2027 * Experience with a scientific computing language (such as Python, R, etc ...

adMarketplace

Data Analyst

Manhattan, NY · On-site

$70K - $90K/yr

Design, execute, and interpret experiments (e.g., A/B testing, causal inference methods) to ... Summer Fridays, catered lunches, a fully stocked kitchen, ZogSports teams, happy hours and ...

Upstart

Principal Applied Scientist

Working knowledge of causal inference or causal machine learning * Strong grounding in statistics ... Summer 2026!) For roles based in Canada, please note that we are not currently able to hire in ...

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Summer Causal Inference information

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$17

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How much do summer causal inference jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for summer causal inference in the United States is $17.40, according to ZipRecruiter salary data. Most workers in this role earn between $13.94 and $20.67 per hour, depending on experience, location, and employer.

What types of projects and methodologies can I expect to work on as a Summer Causal Inference intern?

As a Summer Causal Inference intern, you'll typically work on projects involving the design and analysis of experiments or observational studies to determine cause-and-effect relationships. You may use methodologies such as propensity score matching, difference-in-differences, instrumental variables, or regression discontinuity designs. Collaboration with data scientists, economists, and business stakeholders is common, as you'll help translate findings into actionable insights. Expect to handle real-world datasets and communicate your results through presentations or reports, gaining valuable experience in both technical and applied aspects of causal inference.

What are the key skills and qualifications needed to thrive as a Summer Causal Inference Researcher, and why are they important?

To thrive as a Summer Causal Inference Researcher, you need a solid background in statistics, econometrics, and data analysis, typically supported by coursework or a degree in a quantitative field. Familiarity with statistical programming languages like R or Python and experience using tools such as STATA or MATLAB are often required. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are valuable soft skills. These skills and qualities are crucial for accurately identifying causal relationships in data and effectively collaborating within interdisciplinary research teams.

What is a Summer Causal Inference position?

A Summer Causal Inference position is typically a short-term research or internship role focused on applying statistical methods to determine causal relationships between variables, often in fields like economics, public policy, or data science. Individuals in this position work on projects that require designing experiments or analyzing observational data to infer causality rather than just correlation. The role is ideal for students or early-career professionals seeking hands-on experience in causal inference techniques during the summer months.
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Summer Causal Inference jobs near you

Senior Product Manager

Smadex SLU

New York, NY • On-site

$138K - $182K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 14 days ago

Job description

Smadex is a leading advertising technology company founded in Barcelona in 2010 and sold to American-based and stock-listed Entravision in 2018 (NYSE: EVC). We are one of the top mobile ad-tech companies in the world and the largest Demand Side Platform (DSP) based in Europe, with revenues over +$100M and consistently growing year over year.

As a Senior Product Manager on our measurement and data team, you will own a set of quantitatively deep initiatives that sit close to our bidding, attribution, and data infrastructure. This is a builder role for someone who is comfortable reasoning about causal inference, experimentation, and data quality at scale, and who can turn that reasoning into a product that engineers, data scientists, and commercial teams actually use. You will work directly with our ML, data, and infrastructure teams as a technical peer.

This position is based in Austin, TX or New York, NY.

Role's tasks and responsibilities:

  • Own product strategy and execution for measurement and data initiatives spanning causal measurement, attribution and identity, and the quality and observability of our data and models.
  • Translate causal and statistical methods into product decisions, and partner with data science on how measurement and optimization should behave in production.
  • Define how performance signals are monitored, explained, and surfaced across large, fast-moving datasets so the right people see what changed and why.
  • Work closely with engineering to prioritize development, and align commercial, marketing, and operations teams on timelines and strategy.
  • Set the metrics and experimentation approach for your area, and use them to decide what ships.
  • Stay at the forefront of AdTech, new technologies, industry trends, and privacy regulations.

Role's skills and requirements:

  • Technical degree in a quantitative field such as Engineering, Statistics, Mathematics, Economics, or Data Science.
  • 5+ years in product management or data-heavy product work, including time owning measurement, ML-adjacent, or data-platform products.
  • Strong applied grounding in at least one of: causal inference and incrementality measurement, experimentation and A/B testing, attribution and identity, or large-scale data quality and observability.
  • Fluency with data. You can write SQL, reason about a data model, and work independently in a notebook or query engine to answer your own questions.
  • Comfort engaging directly with model behavior, evaluation, and statistical tradeoffs alongside data scientists and ML engineers.
  • Demonstrated experience in hypothesis-driven learning and turning data into actionable insights.
  • Excellent written communication. You write specs that hold up to technical scrutiny and need little editing before they ship.

Preferred:

  • Experience in programmatic advertising, adtech, or another real-time bidding or marketplace environment.
  • Familiarity with mobile attribution, MMPs, or privacy-driven measurement.

What’s in it for you?

  • Great compensation package tailored to the U.S. market.
  • Career pathing and continued education available 
  • Highly engaged leadership to support you in your position and career
  • Opportunity for international travel
  • Comprehensive medical, dental & vision benefits  
  • 401k matching
  • Summer Fridays & Team building events 

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