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Causal Inference Machine Learning Postdoctoral Jobs in Fort Worth, TX

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 ...

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Causal Inference Machine Learning Postdoctoral information

See Fort Worth, TX salary details

$34K

$52K

$58.5K

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

As of Jul 15, 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, 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?

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

Senior Data Scientist

Starcom Mediavest Group Germany Gmbh

Plano, TX • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 29 days ago

Job description

Company Description

Digitas is the Networked Experience Agency, built on the vision that we create magnetic experiences that earn the right for brands to exist in human networks. Today, and tomorrow. We deliver Networked Experiences by leveraging comprehensive data, technology, creative, media and strategy capabilities. Digitas delivers ambitious outcomes via unique solutions that include Creative Experiences, Integrated Media, Addressable Relationships, Social Marketing and Total Commerce. Celebrated by AdAge as Data and Insights Agency of the Year, U.S Campaign's Brand Experience Agency of the Year, Media Network of the Year and celebrated by Forrester and Gartner, Digitas serves the world's leading brands through a global network comprised of more than 5,500 employees across over 65 offices in 43 countries.

The Digitas culture is made up of fearless, inventive and generous Unicorns of all kinds.

This role at Digitas will serve as a member of Publicis Groupe's strategic internal agency, Constellation.

Constellation serves as an internal-facing brand formed by a collective of Publicis Groupe agencies to address our client's creative, data, strategy, media, and technology requirements. Team members collaborate across agencies while functioning as sub-divisions within their respective brands to provide dedicated support for the client. By acting as a unified interface, Constellation eliminates operational silos and presents a single service entity and primary point of contact for the client.

Job Description

The Data Science team uses data-driven insights and recommendations to fuel strategic growth for clients through building industry-leading analytical solutions. We apply bespoke and cutting-edge arsenal of analytical, statistical and machine learning techniques to complex problems at scale, with an emphasis on game-changing and measurable business impact. We work in close collaboration with colleagues across all agency disciplines to develop truly innovative, highly effective, data-powered solutions for our clients.

We're seeking a Senior Data Scientist who is intellectually curious, creative, and eager to solve both familiar and novel data challenges. If you thrive on turning data into actionable insights and enjoy working in a fast-paced, collaborative environment, we want to hear from you.

Responsibilities

As a Senior Data Scientist, you'll partner with the business leaders and diverse stakeholders to solve complex marketing challenges and deliver impact - from cross-channel media and customer experience optimization to segmentation, targeting and business strategy - through analytics, machine learning and statistical methods.

Day-to-day, your role includes:

  • Translate complex marketing and business questions into clear, actionable analytical plans.
  • Conduct extensive exploratory and statistical analyses to uncover actionable insights.
  • Apply advanced machine learning, causal inference, and statistical techniques to optimize marketing strategies, campaign effectiveness, and customer experiences.
  • Build and test scalable data pipelines and models for real-time applications.
  • Summarize, visualize, communicate and document analytic concepts, processes and results for technical and non-technical audiences
  • Collaborate cross-functionally to define analytical objectives, approaches, and timelines, ensuring alignment on goals and impact.
  • Facilitate ownership and accountability by ensuring that the team is producing trustworthy and high-quality outputs that influence the decisions and direction of a variety of business areas.
  • Proactively explore trends in marketing and digital performance and stay up-to-date with latest AI/ML advancements to surface future opportunities.
  • Share knowledge, debate techniques, and conduct research to advance the collective knowledge and skills of our Data Science practice.
  • Work independently and drive your own projects.
Qualifications
  • MS or PhD in Computer Science, Statistics, Mathematics, or a related field
  • +4 years of industry experience in data science and marketing field
  • Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
  • Experience in media performance analytics such as attribution modeling, incrementality testing and advance measurement methodologies.
  • Proficiency in common data science coding languages such as in SQL, Python and/or R (Spark is preferred)
  • Practical experience with Google Cloud Platform and services such as BigQuery, Looker, and DataProc
  • Exceptional communication and presentation skills with technical and non-technical audiences; highly effective at developing meaningful stakeholder relationships and deep domain expertise.
  • Comfort with ambiguity; ability to thrive with minimal oversight and process.
  • Embodies Digitas values while bringing a new perspective to continue improving our culture.
Additional Information

Our Publicis Groupe motto "Viva La Difference" means we're better together, and we believe that our differences make us stronger. It means we honor and celebrate all identities, across all facets of intersectionality, and it underpins all that we do as an organization. We are focused on fostering belonging and creating equitable & inclusive experiences for all talent.

Publicis Groupe provides robust and inclusive benefit programs and policies to support the evolving and diverse needs of our talent and enable every person to grow and thrive. Our benefits package includes medical coverage, dental, vision, disability, 401K, as well as parental and family care leave, family forming assistance, tuition reimbursement, and flexible time off.

If you require accommodation or assistance with the application or onboarding process specifically, please contact USMTTACompliance@publicis.com.

All your information will be kept confidential according to EEO guidelines.

 Compensation Range: USD $88,540.00 - USD $127,155.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 8/15/2026.Employment Type: FULL_TIME

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