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Remote Causal Inference Jobs in Dallas, TX (NOW HIRING)

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How much do remote causal inference jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for remote causal inference in Dallas, TX is $56.20, according to ZipRecruiter salary data. Most workers in this role earn between $46.15 and $66.59 per hour, depending on experience, location, and employer.

What is a Remote Causal Inference job?

A Remote Causal Inference job involves using statistical and analytical methods to determine cause-and-effect relationships from data, often for fields like healthcare, social sciences, or business. Professionals in this role work remotely, leveraging tools such as R, Python, or specialized software to analyze experiments, observational studies, or large datasets. Their insights help organizations make data-driven decisions, design better interventions, and accurately measure the impact of policies or treatments. Strong skills in statistics, machine learning, and communication are essential for success in this position.

What are the key skills and qualifications needed to thrive as a Remote Causal Inference Specialist, and why are they important?

To thrive as a Remote Causal Inference Specialist, you need strong quantitative and statistical skills, a solid background in econometrics or data science, and typically an advanced degree in a related field. Proficiency with statistical programming languages such as R or Python, experience with causal inference frameworks like propensity score matching or instrumental variables, and familiarity with data visualization tools are crucial. Outstanding problem-solving abilities, clear communication, and self-motivation are essential soft skills for working independently and conveying complex results to non-technical stakeholders. These skills enable accurate, actionable insights from data, which drive evidence-based decision-making in remote, collaborative environments.

How does a remote Causal Inference specialist typically collaborate with cross-functional teams, and what tools are commonly used?

As a remote Causal Inference specialist, you’ll frequently work with data scientists, product managers, and engineers to design and interpret experiments, analyze observational data, and provide actionable insights. Collaboration usually happens through regular video meetings, shared documentation, and project management tools. Commonly used platforms include Slack or Microsoft Teams for communication, GitHub for code collaboration, and Jupyter Notebooks or RMarkdown for sharing reproducible analyses. These tools help ensure transparency and maintain strong teamwork despite the remote environment.
What are the most commonly searched types of Causal Inference jobs in Dallas, TX? The most popular types of Causal Inference jobs in Dallas, TX are:
What are popular job titles related to Remote Causal Inference jobs in Dallas, TX? For Remote Causal Inference jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Remote Causal Inference jobs in Dallas, TX look for? The top searched job categories for Remote Causal Inference jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Causal Inference jobs? Cities near Dallas, TX with the most Remote Causal Inference job openings:
Remote Causal Inference jobs near you
Infographic showing various Remote Causal Inference job openings in Dallas, TX as of June 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 100% Remote job distribution, with an average salary of $116,898 per year, or $56.2 per hour.

Data Scientist/ Product Analytics

TECHOAUTH SOLUTIONS LLC

Fort Worth, TX • Remote

$123K - $174K/yr

Full-time

Posted yesterday

Job description

Job: Data Scientist/ Product Analytics
Location: Remote
Employment Type: Full-Time
About the Role
We are looking for a Data Scientist who will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation. This person will partner closely with product, engineering, design, and business stakeholders to identify opportunities, define success metrics, analyze user behavior, and turn data into practical recommendations.
This role is ideal for a senior individual contributor who enjoys ambiguous problems, can move quickly in a startup environment, and can balance hands-on execution with strategic guidance.
What You Will Do
Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention
Define and maintain clear metrics that help the company understand product health, customer behavior, and business performance.
Design, analyze, and interpret experiments and quasi-experiments to guide product and investment decisions.
Build dashboards, recurring reporting, and lightweight self-serve tools that help product and business teams answer common questions faster.
Create reliable datasets and partner with engineering to improve event tracking, data quality, and analytical foundations.
Translate complex analyses into clear narratives, recommendations, and tradeoffs for technical and non-technical audiences.
Partner cross-functionally with product, engineering, design, marketing, and leadership to ensure insights are used in decision-making.
Mentor other analysts or data scientists as the team grows, and help establish strong practices for metrics, experimentation, and analytical review.
What We Are Looking For
6+ years of experience in data science, product analytics, applied statistics, or a closely related role. More senior experience is welcome.
Strong SQL skills and experience working with relational databases, event data, and product usage data.
Hands-on experience with Python or R for analysis, modeling, experimentation, and data visualization.
Experience defining metrics, building dashboards, and developing analytical frameworks that support product and business decisions.
Strong understanding of experimentation, A/B testing, causal inference, and common statistical methods used in product decision-making.
Ability to work independently in ambiguous environments and turn broad business questions into structured analysis plans.
Strong communication skills, including the ability to explain findings clearly to executives, product managers, engineers, and non-technical stakeholders.
A practical, startup-oriented mindset with strong ownership, urgency, and a bias toward action.

Preferred Qualifications

Advanced degree in Statistics, Mathematics, Economics, Computer Science, Operations Research, Physics, or a related quantitative field.
Experience in consumer products, marketplaces, social platforms, growth, or another data-rich product environment.
Experience creating analytical roadmaps, leading cross-functional measurement strategy, or advising senior leadership.
Experience building or improving data pipelines, semantic layers, experimentation platforms, or product analytics infrastructure.
Experience mentoring analysts or data scientists and raising the quality of analytical work across a team.

Compensation and Benefits
Competitive salary, based on experience, role scope, location, and applicable legal requirements.

This is a remote position.