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Statistical Data Analysis Jobs in Texas (NOW HIRING)

Top 3 Keywords: 1- Process Capability Analysis & Statistical Data Tracking 2- Deviation Management (Root Cause & Corrective Actions) 3- Microsoft Office (Advanced Excel) Top Required Skills:

Data Analysis Tutor

Allen, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Austin, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Bryan, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Houston, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Dallas, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Lubbock, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Data Analysis Tutor

Irving, TX ยท Remote

$40/hr

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

Ability to explain data types, summary statistics, correlation analysis, and visualization best practices while preparing students for business analysis roles, analytics positions, and data-driven ...

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Statistical Data Analysis information

See Texas salary details

$7

$33

$60

How much do statistical data analysis jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for statistical data analysis in Texas is $33.83, according to ZipRecruiter salary data. Most workers in this role earn between $21.35 and $44.18 per hour, depending on experience, location, and employer.

What is statistical data analysis?

Statistical data analysis is the process of collecting, organizing, interpreting, and presenting numerical data using statistical methods. It helps researchers and professionals identify patterns, trends, and relationships within data sets, enabling informed decision-making. Common techniques include descriptive statistics, hypothesis testing, regression analysis, and data visualization. Statistical data analysis is widely used in fields such as business, healthcare, social sciences, and engineering to draw meaningful conclusions from data.

Are statisticians highly paid?

Statisticians typically earn higher-than-average salaries due to their specialized skills in data analysis, modeling, and statistical software. Salaries vary based on experience, education, industry, and location, but the profession is generally considered well-compensated within the data analysis field.

What does a statistical data analyst do?

A statistical data analyst collects, processes, and interprets large datasets to identify trends and support decision-making. They use statistical software and techniques to analyze data, create reports, and communicate findings to stakeholders, often requiring strong analytical skills and knowledge of tools like Excel, R, or Python.

What is the difference between Statistical Data Analysis vs Data Scientist?

AspectStatistical Data AnalysisData Scientist
Required CredentialsDegree in Statistics, Mathematics, or related fieldDegree in Computer Science, Statistics, or related field
Work EnvironmentResearch labs, finance, healthcare, academiaTech companies, finance, e-commerce, startups
Employer & Industry UsageUsed across industries for analyzing data setsUsed for building predictive models and data-driven products

Statistical Data Analysis focuses on interpreting data using statistical methods, often emphasizing hypothesis testing and descriptive statistics. Data Scientists combine statistical analysis with programming and machine learning skills to create predictive models and extract insights from large, complex data sets. While both roles analyze data, Data Scientists typically have broader technical skills and work on developing algorithms, whereas Statistical Data Analysts concentrate on statistical techniques and reporting.

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

To thrive as a Statistical Data Analyst, a solid background in statistics, mathematics, and data interpretation is required, often supported by a degree in statistics, mathematics, or a related field. Expertise in statistical software such as R, Python, SAS, or SPSS, along with experience in data visualization tools, is typically essential. Strong analytical thinking, attention to detail, and effective communication skills help analysts present complex findings clearly to stakeholders. These competencies are crucial for extracting actionable insights from data and supporting informed, data-driven business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and making informed recommendations. Data analysts who develop skills in machine learning, programming, and data visualization are better positioned to adapt to these technological changes.

Is 40 too late for data science?

Statistical Data Analysis is a key skill in data science, and individuals can successfully transition into the field at age 40 or later. Many data scientists have diverse backgrounds and acquire necessary skills such as programming, statistics, and machine learning through online courses or certifications at any age.

What are some common challenges faced by professionals in statistical data analysis roles, and how can they be addressed?

Professionals in statistical data analysis often encounter challenges such as dealing with incomplete or messy datasets, selecting appropriate statistical methods, and ensuring the reproducibility of their analyses. Overcoming these obstacles typically involves rigorous data cleaning, continuous learning about statistical techniques, and using version control systems for code and data. Collaboration with subject matter experts and maintaining clear documentation are also essential for ensuring that findings are accurate and actionable.
What are the most commonly searched types of Statistical Data Analysis jobs in Texas? The most popular types of Statistical Data Analysis jobs in Texas are:
What job categories do people searching Statistical Data Analysis jobs in Texas look for? The top searched job categories for Statistical Data Analysis jobs in Texas are:
Healthcare Statistical Data Scientist

Healthcare Statistical Data Scientist

SmartLight Analytics

Plano, TX โ€ข On-site, Remote

Full-time

Posted 22 hours ago


Job description

Overview
We're seeking a Machine Learning Data Scientist with deep expertise in healthcare claims data to design, build, and deploy advanced analytics and machine learning modeling solutions. In this role, you'll transform complex administrative and clinical datasets into actionable insights that improve cost efficiency, care quality, and operational performance across the healthcare ecosystem.
You'll collaborate with data engineers, clinicians, and product teams to develop predictive models, optimize workflows, and support strategic decision-making. This position is ideal for someone who thrives at the intersection of data science, healthcare operations, and modern machine learning.
Key Responsibilities
Machine Learning & Advanced Analytics
  • Develop, train, and deploy ML models for use cases such as:
  • Claims cost prediction and utilization forecasting
  • Fraud, waste, and abuse detection
  • Risk adjustment and member stratification
  • Provider performance and network optimization
  • Apply modern ML techniques including gradient boosting, deep learning, NLP, and probabilistic modeling.
  • Capable of applying advanced predictive analytics to correlate disparate datasets and events and derive business value.
  • Build scalable pipelines for feature engineering, model training, validation, and monitoring.

Healthcare Claims Expertise
  • Analyze and interpret medical, pharmacy, and dental claims (CPT/HCPCS, ICD-10, DRG, NDC).
  • Translate domain knowledge into meaningful features and model strategies.

Cross-Functional Collaboration
  • Partner with clinicians, product managers, and business stakeholders to define problems and measure outcomes.
  • Communicate complex analytical findings in clear, actionable terms.

Required Qualifications
  • Strong proficiency in Python and ML libraries (scikit-learn, XGBoost, TensorFlow/PyTorch).
  • Hands-on experience with healthcare claims datasets and coding systems.
  • Solid understanding of statistical modeling, machine learning algorithms, and data mining techniques.
  • Strong knowledge and expertise working with SQL.
  • Ability to translate business needs into analytical solutions.
  • Must have demonstrated the ability to solve complex problems with minimal direction.

Preferred Qualifications
  • Experience with NLP applied to clinical notes or unstructured healthcare data.
  • Familiarity with actuarial concepts, risk scoring, or value-based care models.
  • Familiarity deploying models into production (MLOps, CI/CD).
  • Background in health economics, epidemiology, or biostatistics.
  • Prior work with FHIR, HL7, or interoperability standards.

SmartLight Analytics was formed by a group of industry insiders who wanted to make a meaningful impact on the rising cost of healthcare. With this end in mind, SmartLight combats fraud, waste, and abuse in healthcare through our proprietary data analysis and model development. Requiring the bare minimum in employer involvement, our process works behind the scenes to save money without interrupting employee benefits or requiring employee behavior changes.