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Statistical Inference Jobs (NOW HIRING)

Haystack News

Senior Data Scientist

Fort Lauderdale, FL · Remote

In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user ...

Exponent Inc.

Statistical Scientist (Ph.D.)

Bellevue, WA · On-site

$133K - $150K/yr

Participating in diverse projects involving exploratory data analysis, statistical inference, and predictive modeling * Applying risk analysis methodologies to problems in engineering, health ...

Alutiiq

Operations Research Analyst

El Segundo, CA

$215K - $250K/yr

... statistical inference, decision analysis, agent-based modeling) Strong written and verbal communication; demonstrated ability to brief senior Government audiences Preferred Qualifications Master's or ...

WorldQuant

AI Scientist

New York, NY · Hybrid

$150K - $200K/yr

Ability to run experiments and perform statistical inference. * Experience with software development tools and practices, such as version control (e.g., Git), continuous integration, and testing ...

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Statistical Inference information

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$14

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$80

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.
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What job categories do people searching Statistical Inference jobs look for? The top searched job categories for Statistical Inference jobs are:
Statistical Inference jobs near you
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.
Senior Data Scientist

Senior Data Scientist

Haystack News

Fort Lauderdale, FL • Remote

Full-time

Re-posted 2 days ago

Job description

Haystack News, the number one destination for news on streaming platforms, is looking for a Sr Data Scientist to join our team. Haystack is trusted by over 30 million viewers and is among the fastest-growing TV news companies in the world.

Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user engagement and retention, directly impacting our product's success. This is an exceptional opportunity to showcase your robust problem-solving capabilities and to thrive in a collaborative environment, working alongside a team of passionate professionals dedicated to innovation and excellence. Be part of a dynamic workplace where your contributions make a meaningful difference and help shape the future of news consumption.

MINIMUM QUALIFICATIONS

  • PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field

  • 3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).

  • Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.

  • Proficiency in causal inference methods to measure product impact.

  • Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.

  • Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.

  • Strong experience with SQL (e.g. postgres, snowflake, etc).

PREFERRED QUALIFICATIONS:

  • Experience working on consumer-facing products with millions of users.

  • Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).

  • Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.

  • Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.

RESPONSIBILITIES

  • Build statistical and machine learning models to improve content discovery and user engagement.

  • Work closely with ML engineers to translate models and insights into production systems.

  • Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.

  • Apply causal inference methods to understand the impact of potential product changes.

  • Define and build new ML features using text and multimodal embeddings and GenAI.

  • Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.