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Ai Causal Inference Jobs (NOW HIRING)

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B testing, Git Actions, Tableau, Power BI, ThoughtSpot, Web Scraping * Data & Engineering - SQL ...

... strong causal inference expertise to join the Community Support Data Science team. You'll partner closely with the area's tech lead on high-impact projects spanning AI-powered products ...

Classical AI, knowledge representation via ontology, knowledge graphs and graph neural networks, automated reasoning systems, search and planning algorithms, causal inference and causal modeling ...

Advanced Statistical & Causal Inference: Apply deep knowledge of experimental design, regression, classification, causal inference (difference-in-differences, propensity scores, instrumental ...

Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling. * Expertise in A/B ...

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Ai Causal Inference information

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How much do ai causal inference jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for ai causal inference in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $46.63 and $67.31 per hour, depending on experience, location, and employer.

What is an AI causal inference professional?

AI Causal Inference professionals specialize in using artificial intelligence and statistical methods to determine cause-and-effect relationships within data. Unlike traditional data analysts who may focus on correlations, these experts design experiments or apply mathematical models to uncover how changes in one variable influence another. Their work is crucial in fields like healthcare, economics, and social sciences, where understanding causality can inform better decisions and policies. They often use tools like causal diagrams, randomized controlled trials, and advanced machine learning techniques to draw robust conclusions.

What are the key skills and qualifications needed to thrive as an AI causal inference specialist?

To thrive as an AI Causal Inference Specialist, you need a strong background in statistics, machine learning, and causal modeling, typically supported by an advanced degree in a quantitative field. Familiarity with programming languages like Python or R, experience with causal inference libraries (such as DoWhy or CausalNex), and knowledge of statistical software are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex results and collaborate across multidisciplinary teams. These skills ensure accurate causal analysis, actionable insights, and reliable decision-making in data-driven environments.

What are some common challenges faced by professionals working in AI causal inference, and how can they be addressed?

Professionals in AI causal inference often encounter challenges such as dealing with incomplete or biased data, distinguishing correlation from true causation, and communicating complex findings to non-technical stakeholders. Addressing these challenges typically involves leveraging robust statistical methods, collaborating closely with domain experts, and maintaining transparency in modeling decisions. Continuous learning and staying updated with the latest research can also help navigate the rapidly evolving landscape of AI causal inference.

What other helpful pages are available for Ai Causal Inference?

Other pages related to Ai Causal Inference:

Infographic showing various Ai Causal Inference job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $118,171 per year, or $56.8 per hour.

Senior Manager, Applied Science, Prime Video Advertising

New York, NY • On-site

Amazon
IT Services • 10K+ employees

$164K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,166 frontline employees who took The Breakroom Quiz


Job description

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports - including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.
Are you interested in shaping the future of entertainment and advertising? Prime Video's technology teams are creating best-in-class digital video experiences, and our Advertising Product & Technology organization is at the forefront of revolutionizing the streaming advertising landscape.
The Prime Video Advertising team delivers ad tech solutions that power Prime Video's rapidly growing advertising business across video-on-demand (VOD), live streaming, and display ads-delivering value to both advertisers and viewers worldwide. We focus on critical areas including ad delivery, machine learning-driven optimization, experimentation, audience measurement, and generative AI-powered ad creative solutions.
We are seeking a Senior Manager, Applied Science to lead a team of scientists and engineers building machine learning and AI solutions that directly impact Prime Video's advertising business. In this role, you will own the science strategy and execution for key workstreams including:
- Ad Load Optimization - Balancing advertising revenue with viewer engagement through sophisticated ML models that determine optimal ad frequency, placement, and duration
- Yield Optimization - Maximizing advertising revenue through intelligent allocation, pricing, and forecasting models
- Experimentation & Metrics - Designing and scaling experimentation frameworks and causal inference methods to measure the impact of advertising decisions on both business outcomes and customer experience
- Ad Creative Generation & Augmentation - Leveraging generative AI to create, personalize, and enhance ad creatives at scale
As a leader of leaders, you will set the 3-5 year scientific vision for your organization, build and develop a high-performing team of senior scientists and managers, and drive large-scale ML/AI initiatives that inform strategic decisions for one of the world's largest streaming advertising platforms. You will collaborate closely with engineering, product, and business teams to translate complex scientific capabilities into measurable business impact during a period of rapid growth with a path to $10B in advertising revenue.
This role offers the unique opportunity to shape the science strategy for a new and fast-growing business, working at the intersection of machine learning, generative AI, causal inference, and advertising technology at Internet scale.
BASIC QUALIFICATIONS
- PhD in Computer Science, Computer Engineering, Machine Learning, Statistics, Operations Research, or a related quantitative field
- Experience as a science manager, with demonstrated experience managing other managers or leading science teams through senior leaders
- Extensive track record of solving complex business problems with machine learning, deep learning, and ML engineering at scale
- Proven ability to hire, develop, and manage a high-performing applied science organization, including growing future science leaders
- Experience delivering a scientific vision with a path to execution, including managing strategic research projects spanning multiple years
- Strong technical depth in machine learning with the ability to evaluate and guide work across optimization, causal inference, NLP/generative AI, and recommendation systems
- Experience driving large-scale scientific efforts and making trade-offs between opportunity, resources, and business impact
PREFERRED QUALIFICATIONS
- Experience in advertising technology, ad marketplaces, or revenue optimization domains
- Experience building and deploying large-scale machine learning and AI solutions at Internet scale, particularly in real-time bidding, auction optimization, or content personalization
- Experience with generative AI / large language models applied to creative generation, content augmentation, or personalization
- Track record of managing hybrid science/engineering teams and driving end-to-end ML systems from research to production
- Experience designing and scaling experimentation platforms or causal inference frameworks
- Demonstrated ability to drive 3-5 year strategic initiatives and provide critical inputs into organizational planning (OP1/OP2)
- Active engagement with the external scientific community (publications in ACM, IEEE, NeurIPS, ICML, KDD, or similar venues)
- Proven ability to communicate rigorous scientific concepts and trade-offs to senior leadership and cross-functional stakeholders through verbal and written narratives
- Ability to manage multiple priorities and create a sense of urgency in a fast-paced, high-growth environment
- Experience influencing technical roadmaps and goals across multiple organizations
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 240,600.00 - 325,500.00 USD annually
USA, VA, Arlington - 218,800.00 - 295,900.00 USD annually
USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US