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Statistical Inference Jobs (NOW HIRING)

Must have two (2+) years of experience with predictive models, statistical inference and deep learning * Must have experience using libraries like tensorflow or pytorch * Must have experience ...

Must have two (2+) years of experience with predictive models, statistical inference and deep learning * Must have experience using libraries like tensorflow or pytorch * Must have experience ...

Includes identifying requirements, understanding tool capabilities, and applying sound principles of statistical inference to ensure accuracy and translating results into specific business actions.

Includes identifying requirements, understanding tool capabilities, and applying sound principles of statistical inference to ensure accuracy and translating results into specific business actions.

Must have two (2+) years of experience with predictive models, statistical inference and deep learning * Must have experience using libraries like tensorflow or pytorch * Must have experience ...

Senior Statistical Analyst

Birmingham, AL · On-site

$81K - $100K/yr

Strong applied statistics: hypothesis testing, regression, causal inference, power analysis, experiment design * Experience designing and implementing tracking plans and event instrumentation ...

Principal Data Scientist

Oakland, CA · On-site

$128 - $148/hr

Expertise in experimental design and causal inference methods. * Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessment. * Relevant ...

Conduct deep dive analysis to understand performance bottlenecks in current evaluation methodologies, propose and prototype improvements in metrics, sampling strategy, statistical inference, etc.

Customer Pay Support Rep

Orlando, FL

$15 - $20.25/hr

Work with mathematical concepts such as probability and statistical inference * Apply fundamental concepts such as fractions, percentages, ratios, and proportions to practical situations * Define ...

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Statistical Inference information

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How much do statistical inference jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for statistical inference in the United States is $56.31, according to ZipRecruiter salary data. Most workers in this role earn between $41.11 and $71.88 per hour, depending on experience, location, and employer.

What is the difference between Statistical Inference vs Data Analyst?

AspectStatistical InferenceData Analyst
Primary FocusDrawing conclusions from data samplesAnalyzing and interpreting data to inform business decisions
Skills & CertificationsStatistics, probability, hypothesis testing, certifications like SAS or RData visualization, SQL, Excel, often with certifications like Microsoft Excel or Tableau
Work EnvironmentResearch institutions, academia, data science teamsBusiness, marketing, finance departments
Usage in IndustryDesigning experiments, making inferences about populationsReporting insights, creating dashboards, data cleaning

While both roles involve working with data, Statistical Inference focuses on making conclusions from data samples using statistical methods, often in research settings. Data Analysts interpret data to support business decisions, emphasizing data visualization and reporting. Understanding these differences helps clarify career paths and job expectations in data-related fields.

What jobs use causal inference?

Statistical inference roles, such as data analysts, data scientists, and econometricians, frequently use causal inference to determine cause-and-effect relationships in data. These jobs often require knowledge of statistical methods, programming skills in R or Python, and experience with experimental or observational study designs.

What is statistical inference?

Statistical inference is the process of using data analysis to deduce properties of an underlying probability distribution. It involves making predictions or generalizations about a population based on a sample. Common methods include hypothesis testing, confidence intervals, and estimation. These techniques help researchers and analysts draw meaningful conclusions from limited data, accounting for randomness and uncertainty.

Is 40 too late for data science?

Statistical inference is a key skill in data science, and age is not a barrier to entering the field. Many data scientists start careers later in life, especially if they develop relevant skills such as programming, statistics, and data analysis through online courses or certifications. Success depends on your ability to learn and adapt, not age.

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

To thrive as a Statistical Inference Specialist, you need strong mathematical and statistical knowledge, a relevant degree (such as statistics, mathematics, or data science), and experience with probability theory and hypothesis testing. Familiarity with statistical software like R, Python (with libraries such as SciPy and statsmodels), and tools like SAS or SPSS is typically required. Critical thinking, problem-solving, and clear communication skills enable you to interpret data accurately and convey findings to various stakeholders. These skills and qualities are crucial for drawing valid conclusions from data, supporting evidence-based decision-making, and ensuring the integrity of research or business analyses.

Is statistician a high paying job?

Statisticians typically earn above-average salaries compared to many other professions, with median annual wages often exceeding the national average. Factors such as experience, education level, industry, and geographic location influence earning potential, and advanced skills in statistical software and data analysis can lead to higher pay.

Is AI replacing statisticians?

Statisticians play a key role in designing experiments, analyzing data, and interpreting results, and AI tools are used to enhance these tasks. While AI automates certain repetitive or computational aspects, statisticians are needed to ensure proper methodology, validate models, and provide expert judgment. The profession evolves with technology, emphasizing skills in data analysis, programming, and domain knowledge.

What are some common challenges faced by professionals working in statistical inference roles?

Professionals in statistical inference often face challenges such as ensuring data quality, dealing with incomplete or messy datasets, and selecting appropriate models for analysis. Interpreting results accurately and communicating complex statistical findings to non-technical stakeholders can also be demanding. Additionally, keeping up with advances in statistical methodologies and software tools is essential for continued professional growth in this field.
More about Statistical Inference jobs
What job categories do people searching Statistical Inference jobs look for? The top searched job categories for Statistical Inference jobs are:
Infographic showing various Statistical Inference job openings in the United States as of July 2026, with employment types broken down into 81% Full Time, 18% Part Time, and 1% Contract. Highlights an 71% Physical, 2% Hybrid, and 27% Remote job distribution, with an average salary of $117,120 per year, or $56.3 per hour.
Research Scientist, Demography and Survey Sciences

Research Scientist, Demography and Survey Sciences

Meta

Menlo Park, CA • On-site

$177K - $247K/yr

Full-time

Re-posted 8 days ago


Meta rating

7.5

Company rating: 7.5 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

135th of 209 rated software companies


Job description

The Demography and Survey Science team's mission is to improve the way we make decisions and measure impact both within and outside of Meta. We collect and analyze rich survey and behavioral datasets to understand new challenges, solve problems, and shape decisions. We are looking for quantitative social scientists with experience answering complex research questions to join us in this effort. Our interdisciplinary team includes those with expertise in statistical inference, survey methodology, causal inference and econometrics, regression modeling, exploratory data analysis, and mathematical demography, among other areas. In this role, you'll own research end-to-end. This means you'll navigate trade-offs while designing projects, proposing appropriate methodologies, analyzing data, and communicating results to broad audiences in order to drive impactful decisions. Qualified candidates may include social scientists, applied statisticians, or other applied researchers with expertise in quantitative research methods, experience working with large datasets and relational databases, and experience with survey methodology (e.g., bias correction, sampling). We are looking for candidates who can demonstrate methodological rigor, demonstrated communication skills, and experience making research design choices that balance competing tradeoffs effectively.
Responsibilities
Help shape the research agenda and drive research projects from end-to-end
• Collaborate with product teams to define relevant questions about survey methodology and quantitative measurement
• Deploy appropriate quantitative methodologies to answer those questions
• Develop novel approaches where traditional methods won't do
• Provide teams with usable measurement strategies and methodologies to meet their product and business decision needs
• Deliver insights and recommendations clearly to relevant audiences
Minimum Qualifications
• 8+ years of experience in quantitative research, survey methodology, or a related field
• Bachelor's, Master's or Ph.D. in the social sciences (e.g., Economics, Political Science, Sociology, Psychology, Communication), or in a quantitative field (e.g., Statistics, Informatics, Econometrics)
• Demonstrated experience in designing original research to address complex questions
• Demonstrated expertise in data manipulation and analysis software and programming languages (Python/R, SQL)
• Expertise and applied experience in measurement (e.g., survey design and analysis, experiment design, bias correction, measurement models, data collection, log data) and statistical inference (e.g., causal, Bayesian, machine learning)
• Experience initiating and driving research projects to completion with minimal guidance
• Experience communicating analyses and results to any audience, including executives
• Demonstrated experience in distilling and communicating research insights to influence the thinking, decision-making, and actions of diverse audiences
Preferred Qualifications
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience with qualitative methods such as focus groups, in-depth interviewing, cognitive testing
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience working with executive or leadership-level stakeholders
• Experience working with online survey panel vendors (e.g., YouGov, Ipsos, Kantar, SSRS)
• Experience translating often abstract stakeholder requests into actionable research plans
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.

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