... machine learning, generative AI, causal inference, and advertising technology at Internet scale.
... machine learning, generative AI, causal inference, and advertising technology at Internet scale.
Quantitative Researcher, Central Execution Desk
New York, NY · On-site
$120K - $200K/yr
... machine learning. Our ongoing investment in top engineering talent and technology ensures our ... Working on causal inference methods * Developing optimization models for various execution ...
Quantitative Researcher, Central Execution Desk
New York, NY · On-site
$120K - $200K/yr
... machine learning. Our ongoing investment in top engineering talent and technology ensures our ... Working on causal inference methods * Developing optimization models for various execution ...
Quantitative Researcher, Central Execution Desk
New York, NY · On-site
$120K - $200K/yr
... machine learning. Our ongoing investment in top engineering talent and technology ensures our ... Working on causal inference methods * Developing optimization models for various execution ...
Quantitative Researcher, Central Execution Desk
New York, NY · On-site
$120K - $200K/yr
... machine learning. Our ongoing investment in top engineering talent and technology ensures our ... Working on causal inference methods * Developing optimization models for various execution ...
... inference, hypothesis testing, causal / incrementality measurement). • Build scalable tools that ... Software Engineering, Machine Learning, and/or Data Science. • Strong general software ...
... inference, hypothesis testing, causal / incrementality measurement). • Build scalable tools that ... Software Engineering, Machine Learning, and/or Data Science. • Strong general software ...
Research Engineer, Machine Learning
New York, NY · On-site
$120K - $180K/yr
Causal inference * Program synthesis and analysis * ML Ops and systems engineering These areas are ... machine learning, computational neuroscience, cognitive science, physics, mathematics.
Research Engineer, Machine Learning
New York, NY · On-site
$120K - $180K/yr
Causal inference * Program synthesis and analysis * ML Ops and systems engineering These areas are ... machine learning, computational neuroscience, cognitive science, physics, mathematics.
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Senior Data Scientist
New York, NY · On-site
Design, build, and deploy machine learning models for ad targeting, ranking, and bidding ... Strong background in incrementality measurement, experimentation, A/B testing, causal inference ...
Senior Data Scientist
New York, NY · On-site
Design, build, and deploy machine learning models for ad targeting, ranking, and bidding ... Strong background in incrementality measurement, experimentation, A/B testing, causal inference ...
Senior Applied Scientist, Credit Risk
New York, NY · On-site
$165K - $228K/yr
Apply methods from machine learning, statistics, causal inference, optimization, and economics to solve core business problems * Generate and communicate data-driven insights that influence product ...
Senior Applied Scientist, Credit Risk
New York, NY · On-site
$165K - $228K/yr
Apply methods from machine learning, statistics, causal inference, optimization, and economics to solve core business problems * Generate and communicate data-driven insights that influence product ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Key job responsibilities Leverage deep expertise in causal inference to develop robust, causally ... machine-learning methods (e.g., boosted regression trees, random forests, neural networks ...
Key job responsibilities Leverage deep expertise in causal inference to develop robust, causally ... machine-learning methods (e.g., boosted regression trees, random forests, neural networks ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models ...
Causal Inference Machine Learning Postdoctoral information
See Hillsborough, NJ salary details
$36.2K - $38.5K
6% of jobs
$38.5K - $40.9K
0% of jobs
$40.9K - $43.3K
0% of jobs
$43.3K - $45.6K
0% of jobs
$45.6K - $48K
1% of jobs
$48K - $50.3K
4% of jobs
$50.3K - $52.7K
9% of jobs
$53.6K is the 25th percentile. Wages below this are outliers.
$52.7K - $55.1K
11% of jobs
The median wage is $56.1K / yr.
$55.1K - $57.4K
42% of jobs
$57.5K is the 75th percentile. Wages above this are outliers.
$57.4K - $59.8K
21% of jobs
$59.8K - $62.2K
5% of jobs
$36.2K
$55.2K
$62.2K
How much do causal inference machine learning postdoctoral jobs pay per year?
As of Aug 20, 2026, the average yearly pay for causal inference machine learning postdoctoral in Hillsborough, NJ is $55,247.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $57,600.00 per year, depending on experience, location, and employer.
What is a causal inference machine learning postdoctoral researcher?
A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.
What are the key skills and qualifications needed to thrive as a causal inference machine learning postdoctoral researcher?
To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.
What are some common challenges faced by causal inference machine learning postdoctoral researchers when integrating causal models with real-world data?
Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.
What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?
| Aspect | Causal Inference Machine Learning Postdoctoral | Data Scientist |
|---|---|---|
| Required Credentials | PhD in statistics, machine learning, or related field | Bachelor's or Master's in data science, computer science, or related field |
| Work Environment | Academic research, research labs, universities | Corporate, tech companies, startups |
| Industry Usage | Research, academia, specialized industry projects | Business analytics, product development, data-driven decision making |
| Common Search/Comparison | Yes | Yes |
The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.
Is it difficult to get a causal inference machine learning postdoctoral position?
Securing a causal inference machine learning postdoctoral position can be competitive due to specialized skills required, such as expertise in statistical methods, programming (e.g., Python or R), and a strong research background. Candidates with relevant publications, strong recommendations, and experience in machine learning frameworks often have better chances, but the availability of such positions varies by institution and funding.
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Hillsborough, NJ look for?
The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Hillsborough, NJ are:
What cities near Hillsborough, NJ are hiring for Causal Inference Machine Learning Postdoctoral jobs?
Cities near Hillsborough, NJ with the most Causal Inference Machine Learning Postdoctoral job openings:
$164K/yr
Full-time
Re-posted 10 days ago
Amazon rating
7.4
Based on 7,098 frontline employees who took The Breakroom Quiz
6th of 39 rated national retailers
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.
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