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Causal Inference Machine Learning Postdoctoral Jobs in Fort Worth, TX

AT&T

Director-Advanced Analytics

Dallas, TX · On-site

By integrating Marketing Mix Models (MMM), causal inference, experimentation, predictive analytics ... AI, machine learning, and next-generation causal modeling techniques Scale Marketing ...

AT and T

Director-Advanced Analytics

Dallas, TX · On-site

By integrating Marketing Mix Models (MMM), causal inference, experimentation, predictive analytics ... AI, machine learning, and next-generation causal modeling techniques Scale Marketing ...

Publicis Groupe Holdings B.V

Data Scientist

Plano, TX · On-site

Leverage machine learning, causal inference methods or statistically sound analyses to drive actionable insights and help shape our understanding of marketing strategy, campaign planning, efficacy ...

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

Contribute to our machine learning repositories and optimize models for performance, scalability, and real‑time inference across edge and cloud environments. * Drive performance optimization and ...

Noblesoft Technologies

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

Machine learning development lifecycle - (Data preparation, Data visualization, Statistical ... AI, Causal Inference, Time series analysis, Forecasting, Anomaly detection, Hypothesis testing, A/B ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Contribute to our machine learning repositories and optimize models for performance, scalability, and real-time inference across edge and cloud environments. * Drive performance optimization and ...

ClifyX

Senior AI/ML Developer

Irving, TX · On-site

The role involves building and deploying machine learning pipelines, developing GenAI solutions ... causal inference. • ONNX/TensorRT model optimization and real time inference experience. • ...

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Causal Inference Machine Learning Postdoctoral information

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

As of Sep 3, 2026, the average yearly pay for causal inference machine learning postdoctoral in Fort Worth, TX is $51,967.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,300.00 and $54,100.00 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.

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 are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Fort Worth, TX?

For Causal Inference Machine Learning Postdoctoral jobs in Fort Worth, TX, the most frequently searched job titles are:

What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Fort Worth, TX look for?

The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Fort Worth, TX are:

What cities near Fort Worth, TX are hiring for Causal Inference Machine Learning Postdoctoral jobs?

Cities near Fort Worth, TX with the most Causal Inference Machine Learning Postdoctoral job openings:

Causal Inference Machine Learning Postdoctoral jobs near you

Data Scientist Lead

American Automobile Association (AAA)

Coppell, TX

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 13 days ago

AAA The Auto Club Group rating

7.4

Company rating: 7.4 out of 10

Based on 283 frontline employees who took The Breakroom Quiz

236th of 315 rated insurance

Job description

Data Scientist Lead

As our Lead Data Scientist, you will act as an internal business consultant to help optimize every facet of this organization. You will solve problems and answer questions - using data - for other departments to help us reduce costs, reduce errors, and be a better organization for our 17 million members.

What You'll Do
Every day, you will help solve business problems presented by stakeholders using data. You will partner with business teams to understand challenges, formulate analytical approaches, and deliver actionable insights that improve operational efficiency, customer experience, and business performance.

You will pull, curate, and analyze data from enterprise data platforms and cloud environments using SQL, Python, or similar tools. You will apply statistical methods, hypothesis testing, causal inference, machine learning, and advanced analytics techniques to identify trends, determine root causes, evaluate business strategies, and measure outcomes.


You will work with large-scale datasets and collaborate closely with data engineers to build scalable analytical solutions. Depending on the business need, your work may include exploratory analysis, dashboard development, predictive modeling, experimentation, causal impact studies, or machine learning solutions deployed into production environments.


You will also design, develop, and maintain machine learning and predictive models that support business decision-making and operational efficiency. As part of your day-to-day responsibilities, you will identify opportunities to automate manual processes, streamline analytical workflows, and develop scalable solutions that improve accuracy, consistency, and speed across the organization. This may include leveraging machine learning, generative AI, intelligent agents, and workflow automation technologies to create data-driven solutions that enhance business processes and user experiences.

You will partner with data engineers and business stakeholders to operationalize models, AI-powered applications, and automated processes, ensuring they are scalable, maintainable, and deliver measurable business value. Using tools such as Tableau, Power BI, or other visualization platforms, you will communicate findings and recommendations to technical and non-technical stakeholders.

You will translate complex analytical concepts into clear business insights and influence decision-making across the organization.

As a senior contributor, you will lead projects, mentor junior data scientists, and help guide cross-functional initiatives from concept through implementation.
Note: This is a hybrid role; the candidate must reside within a 100-mile radius of our Costa Mesa, CA office and be available to work on-site 3 days a week on a regular basis, as well as 2-3 times per month for team meetings and collaboration days.
What You'll Need
To thrive in this role, you must have a strong foundation in statistics, data analysis, and business problem solving. You should be comfortable taking an ambiguous business problem, developing an analytical approach, and translating findings into actionable recommendations.

Required Qualifications

  • Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, Economics, or a related quantitative field.

  • Minimum of 3 years of professional experience in data science, advanced analytics, business analytics, or a related field.

  • Minimum of 1 year of experience leading projects, mentoring team members, or managing cross-functional initiatives.

  • Advanced SQL skills with experience querying and analyzing large datasets.

  • Strong programming experience in Python for data analysis, statistical modeling, and machine learning.

  • Experience working with cloud platforms and modern data ecosystems, including AWS, Google Cloud Platform (GCP), Databricks, Snowflake, or similar technologies.

  • Experience applying statistical techniques such as experimental design, hypothesis testing, statistical inference, regression analysis, causal inference and impact measurement

  • Experience developing, validating, deploying, and monitoring machine learning models in production environments.

  • Experience creating dashboards and visualizations using Tableau, Power BI, or comparable tools.

  • Strong communication skills with the ability to explain technical concepts and analytical findings to non-technical audiences.

Preferred Qualifications

  • Experience in the insurance industry, including claims, underwriting, actuary, or operational analytics.

  • Experience supporting Agile teams and working in a sprint-based development environment.

  • Experience with automation, agentic workflows, and AI-driven business solutions.

#LI-SH1

Remarkable benefits:

Health coverage for medical, dental, vision

401(K) saving plans with company match AND Pension

Tuition assistance

Floating holidays and PTO for community volunteer programs

Paid parental leave

Wellness programs

Employee discounts (membership, insurance,

travel, entertainment, services and more!)

Auto Club Enterprises is the largest club within the national AAA federation. We have nearly 17,000 employees in 24 states helping more than 18 million members. The strength of our organization is our employees. Bringing together and supporting different cultures, backgrounds, personalities, and strengths creates a team capable of delivering legendary, lifetime service to our members. When we embrace our diversity - we win. All of Us! With our national brand recognition, long-standing reputation since 1900, and constantly growing membership, we are seeking career-minded, service-driven professionals to join our team.

"Through dedicated employees we proudly deliver legendary service and beneficial products that provide members peace of mind and value."

AAA is an Equal Opportunity Employer

Our organization participates in E-Verify

What AAA The Auto Club Group employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

American Automobile Association logo

About American Automobile Association

Sourced by ZipRecruiter

The American Automobile Association (AAA), headquartered in Heathrow, Florida, USA, is a reputable force in the automotive and insurance industry. Originating in 1902, it began as a coalition of motor clubs with the common goal of providing better roads and travel conditions for motorists. Today, AAA is a comprehensive, multifaceted organization that offers a range of services, including roadside assistance, auto repair services, travel agency services, and diverse insurance products - Auto, Home, Life and more. A significant principle for AAA is to continuously deliver value to their 61 million members through safety, security and peace of mind. The company's mission and core values focus on championing its members' rights and interests, advocating innovation, integrity, teamwork and respect.

Industry

Non-profits

Company size

10,000+ Employees

Headquarters location

Heathrow, FL, US

Year founded

1902

Social media

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