We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency ... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works ...
Expertise in machine learning, neural networks, and deep learning Excellent writing and ... causal inference, predictive modeling on longitudinal data. Expertise in transformers ...
Expertise in machine learning, neural networks, and deep learning Excellent writing and ... causal inference, predictive modeling on longitudinal data. Expertise in transformers ...
Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Build training and inference code with reproducibility, versioning, and automated testing ...
Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Build training and inference code with reproducibility, versioning, and automated testing ...
Machine Learning Engineer
Minneapolis, MN · On-site
Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Build training and inference code with reproducibility, versioning, and automated testing ...
Machine Learning Engineer
Minneapolis, MN · On-site
Role Summary:- Builds, trains and tunes machine learning models. Translates data science ... Build training and inference code with reproducibility, versioning, and automated testing ...
Senior Machine Learning Engineer
$109K - $149K/yr
Builds, trains and tunes machine learning models. Translates data science experiments into scalable ... Build training and inference code with reproducibility, versioning, and automated testing.
Senior Machine Learning Engineer
$109K - $149K/yr
Builds, trains and tunes machine learning models. Translates data science experiments into scalable ... Build training and inference code with reproducibility, versioning, and automated testing.
Machine Learning Lead Engineer : Fractal AI
$107K - $140K/yr
Developing and deploying scalable tools and services for our clients to handle machine learning training and inference * Understanding application of software engineering rigor and best practices to ...
Machine Learning Lead Engineer : Fractal AI
$107K - $140K/yr
Developing and deploying scalable tools and services for our clients to handle machine learning training and inference * Understanding application of software engineering rigor and best practices to ...
Sr. Principal Data Scientist - Remote
Minnetonka, MN · On-site +1
Apply machine learning, statistical analysis, and optimization techniques to large, complex ... Apply best practices in causal inference, AI/ML, quasi-experimental methods, and forecasting to ...
Sr. Principal Data Scientist - Remote
Minnetonka, MN · On-site +1
Apply machine learning, statistical analysis, and optimization techniques to large, complex ... Apply best practices in causal inference, AI/ML, quasi-experimental methods, and forecasting to ...
Post-Doctoral Associate
$65K - $75K/yr
Prior research in causal inference or innovative trial design and analysis About the Department ... Continuous learning opportunities through professional training and degree-seeking programs ...
Post-Doctoral Associate
$65K - $75K/yr
Prior research in causal inference or innovative trial design and analysis About the Department ... Continuous learning opportunities through professional training and degree-seeking programs ...
Sr. Principal Data Scientist - Remote
Minnetonka, MN · On-site +1
Apply machine learning, statistical analysis, and optimization techniques to large, complex ... Apply best practices in causal inference, AI/ML, quasi-experimental methods, and forecasting to ...
Sr. Principal Data Scientist - Remote
Minnetonka, MN · On-site +1
Apply machine learning, statistical analysis, and optimization techniques to large, complex ... Apply best practices in causal inference, AI/ML, quasi-experimental methods, and forecasting to ...
Epidemiologist
$112K - $145K/yr
Candidates are expected to have a deep understanding of causal inference, bias mitigation, and ... machine learning, digital health, wearables, etc. * Contribute to Epidemiology curriculum ...
Epidemiologist
$112K - $145K/yr
Candidates are expected to have a deep understanding of causal inference, bias mitigation, and ... machine learning, digital health, wearables, etc. * Contribute to Epidemiology curriculum ...
Epidemiologist
Minneapolis, MN · On-site
Candidates are expected to have a deep understanding of causal inference, bias mitigation, and ... machine learning, digital health, wearables, etc. * Contribute to Epidemiology curriculum ...
Epidemiologist
Minneapolis, MN · On-site
Candidates are expected to have a deep understanding of causal inference, bias mitigation, and ... machine learning, digital health, wearables, etc. * Contribute to Epidemiology curriculum ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Machine Learning Engineer- AI Data Platform (Minneapolis, MN)
Minneapolis, MN · On-site
$119K - $143K/yr
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Machine Learning Engineer- AI Data Platform (Minneapolis, MN)
Minneapolis, MN · On-site
$119K - $143K/yr
Design, implement, and maintain scalable data pipelines that support model training, inference, and ... Develop, deploy, and monitor machine learning models using AWS SageMaker, ensuring reliability ...
Senior Data Scientist - Marketing Sponsorships
$70K - $140K/yr
At Huntington, you will leverage machine learning, segmentation, and statistical inference on huge data sets to improve how we understand our customers and the communities we serve. Our goal is to be ...
Senior Data Scientist - Marketing Sponsorships
$70K - $140K/yr
At Huntington, you will leverage machine learning, segmentation, and statistical inference on huge data sets to improve how we understand our customers and the communities we serve. Our goal is to be ...
Machine Learning, Python, ML Pipelines, Model Deployment, Model Serving, Data Engineering, Model ... Build training and inference code with reproducibility, versioning, and automated testing.
Machine Learning, Python, ML Pipelines, Model Deployment, Model Serving, Data Engineering, Model ... Build training and inference code with reproducibility, versioning, and automated testing.
AI and Data Science Engineer III
Minneapolis, MN · On-site +1
$119K - $143K/yr
Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...
AI and Data Science Engineer III
Minneapolis, MN · On-site +1
$119K - $143K/yr
Deliver governed datasets and feature engineering and serving patterns for machine learning training and real-time inference, including online and offline consistency, caching, latency targets, and ...
About the Job We seek a talented and dedicated researcher with a background in machine learning ... for Postdoctoral Candidates website for more information regarding benefit eligibility.
About the Job We seek a talented and dedicated researcher with a background in machine learning ... for Postdoctoral Candidates website for more information regarding benefit eligibility.
Causal Inference Machine Learning Postdoctoral information
See Loretto, MN salary details
$36.7K - $39.1K
6% of jobs
$39.1K - $41.5K
0% of jobs
$41.5K - $43.8K
0% of jobs
$43.8K - $46.2K
0% of jobs
$46.2K - $48.6K
1% of jobs
$48.6K - $51K
4% of jobs
$51K - $53.4K
9% of jobs
$54.3K is the 25th percentile. Wages below this are outliers.
$53.4K - $55.8K
11% of jobs
The median wage is $56.8K / yr.
$55.8K - $58.2K
42% of jobs
$58.3K is the 75th percentile. Wages above this are outliers.
$58.2K - $60.6K
21% of jobs
$60.6K - $63K
5% of jobs
$36.7K
$56K
$63K
How much do causal inference machine learning postdoctoral jobs pay per year?
As of Jun 9, 2026, the average yearly pay for causal inference machine learning postdoctoral in Loretto, MN is $55,998.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,200.00 and $58,300.00 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, and why are they important?
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.
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Loretto, MN look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Loretto, MN are:
Instacart rating
6.7
Based on 29 frontline employees who took The Breakroom Quiz
Job description
We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events.
Overview
Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.
We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.
We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.
About the Team:
This is a general posting for multiple intern roles open across our various ML teams. You can find a blurb on each team below:
Economics Team: The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.
Search & Discovery ML: The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search technology at Instacart. They collaborate on building models that enhance relevance of all shopping surfaces, ranking, and personalization, delivering highly relevant results to users across the Instacart ecosystem. As part of the Search and Discovery ML team, you'll work on one of the most critical aspects of the business, helping customers connect with the right products. We are passionate about solving large-scale search challenges and creating innovative solutions that elevate the customer experience. (Recent publications 1, 2, 3, 4, 5).
Content AI Team: The Content AI team at Instacart works alongside world-class engineers, data scientists, and product managers to advance generative AI, recommendations, and catalog intelligence in grocery ecommerce. We build cutting-edge AI models that power real-time recommendations, feed ranking, and automated content generation, ensuring high-quality and engaging customer experiences. Beyond recommendations, we leverage generative AI and LLMs to enhance and enrich Instacart’s catalog, driving AI-powered product understanding and content creation at scale. As part of Content AI, you'll work on high-impact AI solutions, applying LLMs, agentic systems, and computer vision to tackle complex challenges. We are passionate about pushing the boundaries of generative AI to shape the future of ecommerce. If you're excited about building state-of-the-art AI systems, we’d love to have you on board!
Past internship contributions include:
Tensor-based complementary recommendations, published at IEEE Big Data 2021 (Paper) Enhancing sequence-based recommendations for long-tail products (Blog)
About the Job
Based on your passion and background, you may choose to work in a few different areas:
- Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
- Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
- Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
- Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
- Fraud detection and prevention - Using cost sensitive learning to reduce loss.
- Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
- Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.
About You
Minimum Qualifications:
- Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
- Strong programming (Python, C++) and algorithmic skills.
- Good communication skills. Curious, willing to learn, self-motivated, hands-on.
Preferred Qualifications:
- Ph.D. student at a top tier university in the United States
- Prior internship/work experience in the machine learning space
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.
Offers may vary based on many factors, such as candidate experience and skills required for the role.
What Instacart employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Instacart
Sourced by ZipRecruiter
Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.
Industry
Technology, communication and media
Company size
10,000+ Employees
Headquarters location
San Francisco, CA, US
Year founded
2012