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Causal Inference Jobs in Brooklyn, NY (NOW HIRING)

Roku

Senior Research Data Scientist

New York, NY

$330K - $375K/yr

About the role As a Senior Research Data Scientist on Roku's Data Science team, you will lead the development of a best-in-class causal inference platform that measures and optimizes the true ...

Amazon

Economist, Ads Measurement Science

New York, NY · On-site

We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. We are hiring an ...

Roku

Senior Research Data Scientist

New York, NY · On-site

$330K - $375K/yr

About the role As a Senior Research Data Scientist on Roku's Data Science team, you will lead the development of a best-in-class causal inference platform that measures and optimizes the true ...

Twitch

Data Scientist

New York, NY

Apply causal inference methods where experimentation isn't feasible * Develop models and analyses that inform pricing, segmentation, and revenue optimization * Design, run, and analyze A/B ...

Grubhub

Senior Staff Data Scientist

New York, NY · On-site

Develop causal inference and experimentation frameworks that help Wonder understand which product, operational, and marketplace changes truly drive business impact. * Partner with engineering to ...

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All JobsCausal Inference JobsCausal Inference Jobs in Brooklyn, NY

Causal Inference information

See Brooklyn, NY salary details

$57.8K

$104.3K

$142.5K

How much do causal inference jobs pay per year?

As of Aug 15, 2026, the average yearly pay for causal inference in Brooklyn, NY is $104,342.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,400.00 and $114,100.00 per year, depending on experience, location, and employer.

Is causal inference still relevant?

Causal inference is a vital skill for data analysts and researchers, as it helps determine cause-and-effect relationships in data. It remains highly relevant across industries such as healthcare, economics, and technology, especially with the increasing availability of large datasets and advanced statistical tools like R and Python. Professionals in this field are in demand for designing experiments, analyzing observational data, and informing decision-making processes.

What skills and qualifications are needed for a causal inference position?

Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.

What jobs use causal inference?

Causal inference is used in various roles such as data scientist, epidemiologist, econometrician, and policy analyst. These jobs involve analyzing data to determine cause-and-effect relationships, often using statistical tools and programming languages like R or Python. Professionals in these fields work in industries like healthcare, finance, government, and technology to inform decision-making and policy development.

What are common challenges faced in a causal inference position?

Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.

What is a causal inference?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.

What are the most commonly searched types of Causal Inference jobs in Brooklyn, NY?

The most popular types of Causal Inference jobs in Brooklyn, NY are:

What are popular job titles related to Causal Inference jobs in Brooklyn, NY?

For Causal Inference jobs in Brooklyn, NY, the most frequently searched job titles are:

What job categories do people searching Causal Inference jobs in Brooklyn, NY look for?

The top searched job categories for Causal Inference jobs in Brooklyn, NY are:

Causal Inference jobs near you
Infographic showing various Causal Inference job openings in Brooklyn, NY as of August 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 70% Physical, 2% Hybrid, and 28% Remote job distribution, with an average salary of $104,342 per year, or $50.2 per hour.

Senior Data Scientist, Causal Inference

United States Digital Space LLC

Manhattan, NY • On-site

$148 - $185/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 10 days ago

Job description

At the company, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products.

As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels.

Responsibilities:
  • Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems.
  • Own complex domains and develop long-term roadmaps to maximize business impact.
  • Build statistical pipelines, write production code, and design/analyze experiments.
  • Participate in the science on-call rotation to ensure automated campaigns operate successfully.
Experience:
  • Advanced degree in statistics, economics, mathematics, or equivalent industry experience.
  • 4+ years of industry experience in causal inference or data science.
  • Proven ability to apply statistics to unstructured problems and deliver measurable results.
  • Deep technical expertise in causal inference and tackling challenging measurement problems.
  • Expertise in marketing mix modeling is highly preferred.
  • Expertise in SQL and experience with large-scale data platforms.
  • Proficiency in Python and working within production coding environments.
Benefits:
  • Great medical, dental, and vision insurance options with additional programs available when enrolled.
  • Mental health benefits.
  • Family building benefits.
  • Child care and pet benefits.
  • 401(k) plan with company match to help save for your future.
  • In addition to 12 observed holidays, salaried team members have discretionary paid time off; hourly team members have 15 days paid time off.
  • 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible.
  • Subsidized commuter benefits.
  • Monthly the company credits and complimentary the company Pink membership.

the company is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

the company highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. The company considers working in the office at least 3 days per week to be an essential function of this hybrid role. Hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location.

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