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Statistical Data Scientist Jobs (NOW HIRING)

Statistical Data Scientist Job Location: Edison Job Type: Contract * Design, develop, and implement statistical models and machine learning solutions to solve complex business problems. * Apply deep ...

Data Scientist

Irving, TX · On-site

$65 - $70/hr

We are currently seeking a Data Scientist for our client in the Retail domain. We value our ... This role is ideal for someone who enjoys combining statistical rigor, applied machine learning ...

Duration: 6-12 months Detail Bachelor's degree in Computer Science, Statistics, Data Science, or a related field. Master's degree or higher preferred. Minimum 10 years of professional experience as a ...

Deep understanding of statistical methods including but not limited to Bayes' theorem, Hidden Markov Model, etc. * Translate product ideas into defined data science challenges and solve them.

We are currently seeking a Data Scientist for our client in the Retail domain. We value our ... This role is ideal for someone who enjoys combining statistical rigor, applied machine learning ...

The Level 3 Data Scientist shall possess the following capabilities ... Foundations: (Mathematical, Computational, Statistical). * Data Processing: (Data management and ...

Foundations: (Mathematical, Computational, Statistical). * Data Processing: (Data management and ... computer science, and applications-specific knowledge. * Ability to use analytic modeling ...

Use time-series analysis, statistical signal processing and machine learning techniques to design ... Mentor and guide junior data scientists and interns, fostering their growth by providing technical ...

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Foundations: (Mathematical, Computational, Statistical). * Data Processing: (Data management and ... computer science, and applications-specific knowledge. * Ability to use analytic modeling ...

Data Scientist 3

Annapolis Junction, MD · On-site

$132K - $147K/yr

Foundations: (Mathematical, Computational, Statistical). * Data Processing: (Data management and ... computer science, and applications-specific knowledge. * Ability to use analytic modeling ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

Foundations: (Mathematical, Computational, Statistical). * Data Processing: (Data management and ... computer science, and applications-specific knowledge. * Ability to use analytic modeling ...

... statistical data sets Preferred : • Prior experience supporting Federal law enforcement as a data scientist or data analyst Company : AnaVation is a trusted partner that delivers high-value, cost ...

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Statistical Data Scientist information

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$46K

$165K

$243.5K

How much do statistical data scientist jobs pay per year?

As of May 29, 2026, the average yearly pay for statistical data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Statistical Data Scientist, you need a strong background in statistics, mathematics, and data analysis, typically supported by a degree in a quantitative field. Proficiency with programming languages like Python or R, data visualization tools, and experience using machine learning libraries and statistical software such as SAS or SPSS are highly valuable. Critical thinking, problem-solving, and the ability to communicate complex findings clearly are essential soft skills for this role. These competencies ensure that insights derived from data are accurate, actionable, and effectively inform business or research decisions.

How does a Statistical Data Scientist typically collaborate with cross-functional teams on data-driven projects?

Statistical Data Scientists often work closely with cross-functional teams, including engineers, business analysts, and domain experts, to translate complex data into actionable insights. They play a key role in designing experiments, developing statistical models, and ensuring data integrity. Effective communication is essential, as they must explain technical findings to non-technical stakeholders and adapt their analyses to support business objectives. Regular collaboration through meetings, code reviews, and presentations is common, making teamwork and adaptability vital skills in this role.

What does a Statistical Data Scientist do?

A Statistical Data Scientist uses statistical methods and computational tools to analyze large and complex datasets, uncover trends, and generate actionable insights for organizations. They design experiments, build predictive models, and interpret data to solve business problems or advance scientific research. Their work often involves cleaning and preparing data, choosing appropriate statistical techniques, and communicating findings to stakeholders through reports and visualizations.

Is 30 too late for data science?

A statistical data scientist can start a career at age 30, as the field values skills such as programming, statistical analysis, and machine learning, which can be developed through self-study, bootcamps, or advanced degrees. Many professionals transition into data science later in their careers, and age is generally not a barrier if relevant skills and experience are acquired.

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

AspectStatistical Data ScientistData Analyst
Required CredentialsDegree in Statistics, Data Science, or related field; proficiency in statistical programmingDegree in Statistics, Mathematics, or related field; strong analytical skills
Work EnvironmentResearch-focused, developing models, advanced analyticsBusiness-focused, reporting, data visualization
Employer & Industry UsageTech companies, finance, healthcare, research institutionsRetail, marketing, finance, healthcare

Statistical Data Scientists focus on building complex models and advanced analytics, often requiring specialized statistical knowledge. Data Analysts primarily interpret data, create reports, and support decision-making with descriptive analytics. While both roles require strong analytical skills and familiarity with statistical tools, Statistical Data Scientists typically handle more complex modeling tasks and have a deeper focus on statistical theory.

More about Statistical Data Scientist jobs
What cities are hiring for Statistical Data Scientist jobs? Cities with the most Statistical Data Scientist job openings:
What states have the most Statistical Data Scientist jobs? States with the most job openings for Statistical Data Scientist jobs include:
Infographic showing various Statistical Data Scientist job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 13% Physical, and 87% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Statistical Data Scientist

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


Job description

Location:  This position may be performed remotely, but requires the flexibility and willingness to travel as needed.

The Opportunity

Praxis is seeking an Associate Director, Statistical Data Scientist to lead and execute the development, validation and automation of analytical pipelines and statistical models that support metadata-driven clinical data processing, reporting, and regulatory submissions. 

This is a hands-on technical leadership role, ideal for a senior data scientist or statistical programmer who enjoys coding, problem-solving, and working cross-functionally to bring rigor, reproducibility, and automation to clinical reporting workflows. 

The Associate Director will contribute directly to R/Python development while also setting technical standards, mentoring peers, and ensuring readiness for R-based regulatory submissions. 

Primary Responsibilities

  • Lead the design, development, and validation of R/Python code to automate generation of analytical datasets and TLFs within a metadata-driven pipeline. 
  • Translate SAPs and metadata specifications (YAML/CSV) into executable and reproducible code. 
  • Build and validate R packages and data science tools supporting both exploratory and confirmatory analyses, ensuring full traceability and audit readiness. 
  • Implement and validate statisticall models (e.g., MMRM, ANCOVA, logistic regression) using R packages such as mmrm, emmeans. 
  • Collaborate with IT to integrate data science and statistical programming workflows within Databricks and CI/CD pipelines for continuous validation and reproducibility 
  • Collaborate across programming, biostatistics, and data standards functions to ensure dataset definitions, derivations, and metadata align with controlled standards. 
  • Conduct peer code reviews, unit testing, and automated validation; ensuring deliverables meet submission-quality and reproducibility standards 
  • Mentor and guide team members in best practices for programming, validation, and automation  

Qualifications and Key Success Factors

  • Bachelor's or Master's degree in Statistics, Biostatistics, Data Science, or a related field. 
  • 8+ years of statistical programming experience in the pharmaceutical/biotech industy including hands-on experience with R and/or Python. 
  • Proven experience preparing or supporting R-based regulatory submissions (e.g., R package validation, R-based analysis delivery, or submission readiness) 
  • Strong understanding of CDISC ADaM and SDTM data structures, and their use in analytical workflows 
  • Experience developing and validating reusable R/Python libraries and functions 
  • Proficiency with Git, Bitbucket, and CI/CD automation pipelines 
  • Working knowledge of GxP and Part 11 compliance 
  • Excellent documentation and validation practices 
  • Collaborative and proactive mindset; able to operate independently in a small, agile team. 

Preferred Experience: 

  • Familiarity with YAML/JSON configuration and metadata-driven programming workflows 
  • Prior experience migrating from SAS to R/Python environments 
  • Knowledge of R validation frameworks (e.g., risk-based testing, reproducibility documentation). 
  • Experience with exploratory analytics or visualization in R or Python within a regulated framework. 

The physical and mental requirements of our roles include but are not limited to regular use of a computer, devices or other office equipment, clear communication, and occasional movement.  You'll need comfort with screen work, basic hand coordination, and focus.  Reasonable accommodations may be made to enable individuals with disabilities to perform these functions.

Compensation & Benefits

At Praxis, we believe that taking care of our people (and their people) is important, so we provide a world class benefits package to help you thrive. This includes 99% of the premium paid for medical, dental and vision plans.  We also provide company-paid life insurance, AD&D, disability benefits, and voluntary plans to personalize your coverage.Thinking about the future? We match dollar-for-dollar up to 6% on eligible 401(k) contributions and sweeten the deal with long-term stock incentives and ESPP. We provide a discretionary quarterly bonus, an extremely flexible wellness benefit, generous PTO, paid holidays and company-wide shutdowns. Not to mention, you'll also be joining a phenomenal crew of colleagues who are smart, engaged and inspiring. We aim high, collaborate hard, and produce results. Let's achieve the impossible together! 

To round out our world-class total rewards package, we provide annualized base salary compensation in the range listed below.  This range reflects the base salary the Company reasonably expects to pay for the position at the time of posting. Placement within the range will be based on job-related factors, including experience, qualifications, scope of responsibilities, and demonstrated track record of delivering results in similar roles.