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Causal Inference Machine Learning Postdoctoral Jobs in Smyrna, DE

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Causal Inference Machine Learning Postdoctoral information

See Smyrna, DE salary details

$31K

$47.4K

$53.3K

How much do causal inference machine learning postdoctoral jobs pay per year?

As of Aug 11, 2026, the average yearly pay for causal inference machine learning postdoctoral in Smyrna, DE is $47,353.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,700.00 and $49,300.00 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?

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?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

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.

Causal Inference Machine Learning Postdoctoral jobs near you
Infographic showing various Causal Inference Machine Learning Postdoctoral job openings in Smyrna, DE as of June 2026, with employment types broken down into 4% As Needed, 39% Full Time, 49% Part Time, 4% Temporary, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $47,353 per year, or $22.8 per hour.

Data Domain Architect [Multiple Positions Available]

JPMorgan Chase & Co.

Wilmington, DE • On-site

$61.75 - $79.50/hr

Full-time

Medical, Retirement

Posted 15 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks

Job description


DESCRIPTION:
Duties: Optimize features and AI capabilities for the Chase Digital Assistant and other conversational AI products. Drive NLU model training and optimization for Chase Digital Assistant (CDA), advancing NLU capabilities and conversational AI understanding for improving digital containment within CDA. Manage intent and entity taxonomy development and align cross-functional teams across Product, Engineering, and Analytics. Optimize training data sets to improve data quality, NLU model F1 score, and intent recognition rate for CDA. Partner with Annotation Lead to review and optimize training data and enable meaningful and measurable outcomes. Design extended analytic frameworks and semantic representations to support NLU models. Conduct conversational analysis to identify systemic improvement opportunities and inform product enhancements. Identify design gaps and systemic improvement opportunities within conversation flows for customer journey optimization and improved completion rate within CDA. Work with Product Managers, ML Engineers, and Analytics by providing linguistic expertise and direction for new NLP capabilities including dialogue, ambiguity, and inference. Identify new testing opportunities and conversational strategies. Develop and maintain documentation on Natural Language Understanding processes, guidelines, and best practices. Guide linguists and conversation analysts to scale annotation initiatives, strengthen evaluation processes, and drive conversational AI excellence.
QUALIFICATIONS:
Minimum education and experience required: PhD in Computational Linguistics, Linguistics, or related field of study plus 3 years of experience in the job offered or as Data Domain Architect Lead, Computational Linguist, NLU Specialist, Post Doctoral Research Fellow, Siri Lexical Linguist, Linguist, or related occupation.
Skills Required: This position requires two (2) years of experience with the following: designing and optimizing Natural Language Understanding (NLU) and AI-powered systems throughout the product lifecycle, including model training, testing, and evaluation using advanced machine learning and computational linguistics techniques; building, testing, and refining language models for AI applications; conducting error analysis and quality assurance on datasets to improve model outputs and system reliability; creating and maintain taxonomies, and lexical resources to support intent and entity recognition; processing and analyzing raw text and datasets to support model development and continuous improvement; training, testing, and evaluating model performance using established metrics and methodologies; serving as a subject matter expert in linguistics and computational linguistics, resolving intent and entity overlaps within taxonomies; reviewing and correcting annotation data, performing error analysis, and addressing bugs by collaborating with annotation teams; supporting end-to-end AI product development and deployment utilizing tools and platforms including Notepad++, SpaCy, Python, NLTK, Regex, Bash, Git, and language modeling frameworks; tracking project progress and ensuring alignment across cross-functional teams using project management tools including Jira and SharePoint.
Job Location: 301 N Walnut Street, Wilmington, DE 19801.
Full-Time.
About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.

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