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Causal Inference Machine Learning Postdoctoral Jobs in Fort Worth, TX

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Causal Inference Machine Learning Postdoctoral information

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$34K

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$58.5K

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

As of Aug 7, 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.

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

Goosehead Insurance Agency LLC

Westlake, TX • On-site

$150 - $230/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New

Goosehead Insurance rating

7.4

Company rating: 7.4 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

225th of 303 rated insurance

Job description

About Goosehead

Since 2003, Goosehead Insurance has been disrupting the insurance industry by giving clients the power of choice, utilizing a smarter marketing approach, and delivering world‑class service. This is all powered by our focus on hiring and retaining extraordinary people. Our clients trust us with their most valuable possessions, so we’re more than just a bit selective when it comes to hiring new team members.

Who You Are

You are a curious and experienced Data Scientist who enjoys solving real‑world problems with a hyper‑focus on impact. You’re comfortable owning the full lifecycle of a project — from exploratory analysis to building and deploying models in production. You think critically, communicate clearly, and are passionate about driving measurable outcomes. You thrive in cross‑functional teams and can bridge technical rigor with business context.

Key Responsibilities
  • Define and drive the vision for data science at Goosehead, identifying transformative opportunities across the enterprise.
  • Design, develop, and deploy production‑grade machine learning systems that directly impact strategic priorities, including operational efficiency, intelligent automation, and client personalization.
  • Develop new frameworks and reusable methodologies to advance experimentation, model interpretability, and decision intelligence at scale.
  • Lead and mentor a team of data scientists, fostering a culture of technical excellence, creativity, and continuous learning.
  • Serve as a thought partner to executive leadership, translating business challenges into data science strategies and articulating impact through clear storytelling.
  • Establish and uphold best practices in data science operations — including reproducibility, model governance, and ethical AI principles.
  • Stay ahead of the curve in AI research, LLMs, and emerging technologies; drive adoption of innovations that position Goosehead as an industry leader.
Required Qualifications
  • 8+ years of experience in data science, with a strong portfolio of impactful, end‑to‑end solutions in production environments.
  • Expertise in Python and machine learning libraries (e.g., scikit‑learn, XGBoost, TensorFlow, PyTorch).
  • Deep experience with SQL and manipulating large‑scale datasets across structured and unstructured formats.
  • Demonstrated ability to lead teams and mentor junior scientists while maintaining hands‑on technical expertise.
  • Proven experience framing ambiguous business problems into structured, analytical solutions with measurable ROI.
  • Strong communication skills, with the ability to synthesize complex ideas for both executive and technical audiences.
Preferred Qualifications
  • Experience with cloud platforms (Databricks, Azure, and/or Snowflake), containerization (e.g., Docker), and CI/CD for ML.
  • Advanced understanding of LLMs and generative AI, including fine‑tuning, RAG pipelines, and prompt engineering.
  • Familiarity with causal inference, uplift modeling, or reinforcement learning in real‑world systems.
  • Background in insurance, financial services, or similarly regulated industries.
  • Experience in leading cross‑functional initiatives that combine data engineering, product, and business domains.
Benefits Summary
  • High‑quality voluntary health, vision, disability, life, and dental insurance programs.
  • 401(k) Matching Plan.
  • Employee Stock Purchase Plan.
  • Paid holidays, vacation, and sick leave.
  • Corporate‑sponsored programs to enhance employee physical, financial, mental, and emotional wellness.
  • Financial Solution Program.
Equal Employment Opportunity Statement

Goosehead is an equal‑opportunity employer and complies with all applicable federal, state, and local laws, rules, guidelines, and regulations. Goosehead strictly prohibits and does not tolerate unlawful discrimination against employees, applicants, or any other covered person because of race, color, religion, creed, national origin, ancestry, ethnicity, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender, gender identity, transgender status, age, physical or mental disability, veteran status, uniformed service, genetic information, or any other characteristic protected by applicable law. All applicants for employment and all Goosehead employees are given equal consideration based solely on job‑related factors, such as qualifications, experience, performance, and availability.

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