Staff Data Scientist
Sunnyvale, CA · On-site
... causal inference methodologies across large, complex data sets- Develop AI-native automated solutions to deliver prescriptive insights and proactive alerts- Drive the feature evaluation philosophy ...
Staff Data Scientist
Sunnyvale, CA · On-site
... causal inference methodologies across large, complex data sets- Develop AI-native automated solutions to deliver prescriptive insights and proactive alerts- Drive the feature evaluation philosophy ...
Director, Data Science
Boston, MA · On-site
Fidelity Institutional's AI Center of Excellence (AI CoE) is seeking a Principal Data Scientist to ... Apply causal inference techniques (e.g., uplift modeling, DiD, matched controls) to assess ...
Director, Data Science
Boston, MA · On-site
Fidelity Institutional's AI Center of Excellence (AI CoE) is seeking a Principal Data Scientist to ... Apply causal inference techniques (e.g., uplift modeling, DiD, matched controls) to assess ...
... causal inference, and foundational models, to address high-impact business problems • Establish ... Azure AI Engineer, or similar • Experience with model governance, regulatory compliance, and risk ...
... causal inference, and foundational models, to address high-impact business problems • Establish ... Azure AI Engineer, or similar • Experience with model governance, regulatory compliance, and risk ...
Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI
Cambridge, MA · On-site
$75K/yr
Causal Inference, Fairness, and Trustworthy AI in real-world healthcare applications. Our group actively collaborates with large national and international initiatives, including Mass General Brigham ...
Postdoctoral Research Fellow in Statistical Machine Learning and Biomedical AI
Cambridge, MA · On-site
$75K/yr
Causal Inference, Fairness, and Trustworthy AI in real-world healthcare applications. Our group actively collaborates with large national and international initiatives, including Mass General Brigham ...
Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation. If so, come join Amazon Ads to be ...
Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation. If so, come join Amazon Ads to be ...
Apply causal inference techniques (e.g., uplift modeling,DiD, matched controls) to assess ... Large Language Models & Generative AI: Design, evaluate, and implement LLM-based solutions ...
Apply causal inference techniques (e.g., uplift modeling,DiD, matched controls) to assess ... Large Language Models & Generative AI: Design, evaluate, and implement LLM-based solutions ...
Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation. If so, come join Amazon Ads to be ...
Are you passionate about causal inference, Deep Learning & AI, raising the science bar, and connecting leading-edge science research to Amazon-scale implementation. If so, come join Amazon Ads to be ...
Applied ML Science Manager
Cupertino, CA · On-site
You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... AI to improve productivity and generate new insightsCurious business attitude with an ability to ...
Applied ML Science Manager
Cupertino, CA · On-site
You will be at the forefront of designing, developing, and deploying cutting-edge Causal Inference ... AI to improve productivity and generate new insightsCurious business attitude with an ability to ...
Use advanced ML, causal inference, and generative AI techniques to model and explain complex interactions across the Pinterest ecosystem (e.g., organic engagement, ads, content quality, monetization ...
Use advanced ML, causal inference, and generative AI techniques to model and explain complex interactions across the Pinterest ecosystem (e.g., organic engagement, ads, content quality, monetization ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior ...
Lead the development of causal inference frameworks to quantify the impact of macroeconomic shifts and internal interventions on our global ecosystem. • AI Strategy: Drive the roadmap for ...
Lead the development of causal inference frameworks to quantify the impact of macroeconomic shifts and internal interventions on our global ecosystem. • AI Strategy: Drive the roadmap for ...
You understandhow incrementality testing, ranging from geo-based experiments to causal inference ... Familiarity with Generative AI and large language models, along with a comfort level in integrating ...
You understandhow incrementality testing, ranging from geo-based experiments to causal inference ... Familiarity with Generative AI and large language models, along with a comfort level in integrating ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods (including Causal Graph/Causal AI techniques) and advanced statistical methods. * Experience in AI/ML ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods (including Causal Graph/Causal AI techniques) and advanced statistical methods. * Experience in AI/ML ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods ( including Causal Graph/Causal AI techniques ) and advanced statistical methods. * Experience in AI/ML ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods ( including Causal Graph/Causal AI techniques ) and advanced statistical methods. * Experience in AI/ML ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods (including Causal Graph/Causal AI techniques) and advanced statistical methods. * Experience in AI/ML ...
Advanced knowledge and applied experience with a wide range of Causal Inference methods (including Causal Graph/Causal AI techniques) and advanced statistical methods. * Experience in AI/ML ...
The AI Scientist role involves developing and applying foundation models to large-scale datasets ... Preferred : • Background in causal inference, generative models, or representation learning for ...
The AI Scientist role involves developing and applying foundation models to large-scale datasets ... Preferred : • Background in causal inference, generative models, or representation learning for ...
... and causal inference • Identify and prevent data leakage, overfitting, and other failure modes ... AI or AWS/SageMaker). • MS or PhD in Statistics, Computer Science, Operations Research, or a ...
... and causal inference • Identify and prevent data leakage, overfitting, and other failure modes ... AI or AWS/SageMaker). • MS or PhD in Statistics, Computer Science, Operations Research, or a ...
Ai Causal Inference information
See salary details
$16.59 - $22.49
1% of jobs
$22.49 - $28.39
1% of jobs
$28.39 - $34.29
5% of jobs
$34.29 - $40.19
4% of jobs
$40.19 - $46.09
13% of jobs
$46.49 is the 25th percentile. Wages below this are outliers.
$46.09 - $51.99
12% of jobs
The median wage is $57.30 / hr.
$51.99 - $57.89
16% of jobs
$57.89 - $63.79
18% of jobs
$65.85 is the 75th percentile. Wages above this are outliers.
$63.79 - $69.69
16% of jobs
$69.69 - $75.59
12% of jobs
$75.59 - $81.49
3% of jobs
$16
$56
$81
How much do ai causal inference jobs pay per hour?
As of Jun 9, 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 are AI Causal Inference professionals?
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, and why are they important?
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.
Apple rating
8.1
Based on 661 frontline employees who took The Breakroom Quiz
6th of 30 rated technology retailers
Job description
Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work...Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things...As a Staff Data Scientist, you will set the technical direction for AI-powered and personalized experiences across the Retail Online journey. You will architect advanced models, define evaluation frameworks for product launches, and develop AI-native automated solutions using cutting-edge scientific methods. Operating at the highest technical level, you will partner with engineers, product, and business leaders to drive meaningful customer impact, shape long-term technical vision, and mentor the next generation of data scientists.
Research and define the gold standard for evaluation methods to improve quality of the Retail online journey. Solve the most ambiguous, high-impact analytical problems by applying advanced statistical, ML, and LLM-driven methods- Design, execute, and oversee robust observational and experimental studies, advancing causal inference methodologies across large, complex data sets- Develop AI-native automated solutions to deliver prescriptive insights and proactive alerts- Drive the feature evaluation philosophy, proactively shape the product roadmap with insights, and establish a rigorous culture of experimentation
Masters in Statistics, Mathematics, Data Science, ML, Physics, Engineering, CS or equivalent5+ years of experience as a Data ScientistExpert proficiency in statistical analysis, causal inference, experimentation design, observational methods (DiD, synthetic control, IV, PSM), drift analysis, predictive modeling and heterogeneous treatment effectsProficiency in SQL, Spark or equivalent; Python or R for modeling and analysisExperience building solutions with LLMs prompt engineering, RAG architectures, fine-tuning basics, and model evaluationExcellent communication skills, product intuition and customer pain point awareness
PhD in Statistics, Mathematics, Data Science, ML, Physics, Engineering, Computer Science or in a quantitative fieldPublications or patents in causal inference, ML, or applied statisticsExperience with causal ML methods (CATE estimation via econml/grf, causal forests)Experience building LLM-powered analytical tools, synthetic data generation for training or privacy preservationExperience with recommendation systems and ML ranking models, data architecture, data lakes, streaming vs. batch, and data contracts.Familiar with MLOps: CI/CD for models, Kubernetes, feature stores
Research and define the gold standard for evaluation methods to improve quality of the Retail online journey. Solve the most ambiguous, high-impact analytical problems by applying advanced statistical, ML, and LLM-driven methods- Design, execute, and oversee robust observational and experimental studies, advancing causal inference methodologies across large, complex data sets- Develop AI-native automated solutions to deliver prescriptive insights and proactive alerts- Drive the feature evaluation philosophy, proactively shape the product roadmap with insights, and establish a rigorous culture of experimentation
Masters in Statistics, Mathematics, Data Science, ML, Physics, Engineering, CS or equivalent5+ years of experience as a Data ScientistExpert proficiency in statistical analysis, causal inference, experimentation design, observational methods (DiD, synthetic control, IV, PSM), drift analysis, predictive modeling and heterogeneous treatment effectsProficiency in SQL, Spark or equivalent; Python or R for modeling and analysisExperience building solutions with LLMs prompt engineering, RAG architectures, fine-tuning basics, and model evaluationExcellent communication skills, product intuition and customer pain point awareness
PhD in Statistics, Mathematics, Data Science, ML, Physics, Engineering, Computer Science or in a quantitative fieldPublications or patents in causal inference, ML, or applied statisticsExperience with causal ML methods (CATE estimation via econml/grf, causal forests)Experience building LLM-powered analytical tools, synthetic data generation for training or privacy preservationExperience with recommendation systems and ML ranking models, data architecture, data lakes, streaming vs. batch, and data contracts.Familiar with MLOps: CI/CD for models, Kubernetes, feature stores
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976