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Remote Statistical Programmer Jobs in Riverside, CA

Tunabear

Peoplesoft Payroll Developer

Riverside, CA · Remote

Peoplesoft Payroll Developer * Full time contract (1099/C2C) * 100% remote (PST) Scope of Work ... Experience with configuration strategy preparation, object migration with STAT/PHIRE , procedures ...

TP-Link Systems Inc.

Senior Mobile App Developer

Irvine, CA · Remote

$140K - $200K/yr

Are you a seasoned mobile app developer with a strong track record of building and leading high ... Able to actively listen and establish best practices for remote global development teams. Preferred ...

Invoca

Senior ML Engineer

Anaheim, CA · On-site +1

$109K - $150K/yr

S. in Computer Science, Engineering, Statistics, or equivalent; advanced degree a plus * Familiarity with RLHF or preference training is a bonus 📍 Location This is a remote-first role. We are ...

Corvel

Data Scientist II

Irvine, CA · On-site +1

$82K - $127K/yr

Working closely with product managers, engineering teams, and business stakeholders, this position ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and ...

Corvel

Data Scientist II

Irvine, CA · On-site +1

Working closely with product managers, engineering teams, and business stakeholders, this position ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Mine and ...

Corvel

Data Science Manager

Irvine, CA · On-site +1

This individual has expertise in machine learning, statistical modeling, and data visualization to ... This position is open to remote or hybrid. ESSENTIAL FUNCTIONS & RESPONSIBILITIES: * Design, build ...

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All JobsRemote Statistical Programmer JobsRemote Statistical Programmer Jobs in Riverside, CA

Remote Statistical Programmer information

See Riverside, CA salary details

$88.2K

$153.7K

$259.8K

How much do remote statistical programmer jobs pay per year?

As of Jun 11, 2026, the average yearly pay for remote statistical programmer in Riverside, CA is $153,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,400.00 and $166,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Statistical Programmer, you need strong proficiency in statistics, data analysis, and programming languages like SAS or R, typically supported by a degree in statistics, mathematics, or a related field. Familiarity with statistical software, clinical trial data standards (such as CDISC), and regulatory submission requirements is often necessary. Attention to detail, problem-solving ability, and effective remote communication are essential soft skills for collaborating with cross-functional teams. These competencies ensure high-quality data analysis, regulatory compliance, and seamless teamwork in a remote environment.

How do Remote Statistical Programmers typically collaborate with cross-functional teams despite working remotely?

Remote Statistical Programmers often work closely with biostatisticians, data managers, and clinical research associates using collaborative tools such as video conferencing, project management platforms, and secure data-sharing systems. Regular virtual meetings are scheduled to discuss project progress, address data or programming issues, and align on analysis plans. Clear documentation and version control are essential to ensure seamless teamwork and maintain data integrity. Effective communication skills and proactive updates help bridge the physical distance and contribute to successful project outcomes.

What is the difference between Remote Statistical Programmer vs Clinical Data Analyst?

AspectRemote Statistical ProgrammerClinical Data Analyst
Required CredentialsBachelor's/Master's in Biostatistics, Statistics, or related field; programming skills in SAS, R, or PythonBachelor's/Master's in Statistics, Data Science, or related; strong analytical and statistical skills
Work EnvironmentRemote or office-based, collaborating with biostatistics teams in clinical trialsRemote or on-site, analyzing clinical data to support study outcomes
Employer & Industry UsagePharmaceuticals, biotech, CROs, clinical research organizationsPharmaceuticals, healthcare, research institutions, CROs

Remote Statistical Programmers focus on programming and data management for clinical trials, while Clinical Data Analysts interpret and analyze clinical data. Both roles require strong statistical skills and often work in similar environments within the healthcare and pharmaceutical industries, but their core responsibilities differ.

What Does a Remote Statistical Programmer Do?

As a remote statistical programmer, you use programming techniques to produce useful data sets from raw data. In this role, you may evaluate the programming needs of each project, use validation techniques to ensure the accuracy of all data sets your programs make, and manage both a database and the operating environment of your software. Remote statistical programmers often work from home and collaborate with other programmers through video calls, voice chat, or remote office software. This job is also known as SAS, which stands for statistical analysis system programming, and companies may advertise under either title.

What is a remote statistical programmer?

A remote statistical programmer is a professional who uses statistical software and programming languages to analyze data, typically for research, clinical trials, or business insights, while working from a location outside of a traditional office environment. They are responsible for managing, cleaning, and organizing large datasets, and for developing programs that generate statistical analyses and reports. Remote statistical programmers often collaborate with statisticians, data scientists, and project teams using online communication tools. This role requires strong skills in programming languages such as SAS, R, or Python, and attention to detail when handling complex data. Working remotely provides flexibility but also requires good time management and communication skills.
More about Remote Statistical Programmer jobs
What are the most commonly searched types of Statistical Programmer jobs in Riverside, CA? The most popular types of Statistical Programmer jobs in Riverside, CA are:
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What job categories do people searching Remote Statistical Programmer jobs in Riverside, CA look for? The top searched job categories for Remote Statistical Programmer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Remote Statistical Programmer jobs? Cities near Riverside, CA with the most Remote Statistical Programmer job openings:
Remote Statistical Programmer jobs near you

Machine Learning Engineer (Hybrid- Greenfield Opportunity)

Match Made Tech

Irvine, CA • On-site, Remote

$75 - $95/hr

Other

Posted 5 days ago

Job description

AI/ML Engineer - Greenfield AI Project

UNABLE TO OFFER SPONSORSHIP- US CITIZENS & GREEN CARD ONLY

LOCATION: Irvine, CA (onsite). Monday through Thursday onsite, Fridays remote.

SPONSORSHIP NOT AVAILABLE- MUST BE US CITIZEN/ GREEN CARD HOLDER

COMPENSATION: $75-95 an hour. This is a 2-year contract that will convert to full-time.

About Us

We are on a mission to develop innovative AI solutions that will revolutionize our workforce. As we embark on an exciting new greenfield AI project, we are seeking an exceptional AI/ML Engineer to join our team and lead the development of machine learning models as part of this groundbreaking initiative.

Job Description

About the Role

We are seeking a skilled AI/ML Engineer to join our team to design, develop, and deploy machine learning models that solve real-world business challenges. You will work cross-functionally with data scientists, engineers, and product teams to bring cutting-edge AI solutions to production, with a strong focus on NLP, supervised learning, experimentation, and optimization.

Key Responsibilities
  • Model Development & Training
    • Collaborate with data scientists and stakeholders to translate project goals into scalable ML solutions.
    • Design, develop, and train models using state-of-the-art machine learning techniques and tools.
    • Select appropriate annotated datasets and transform raw data into machine learning-ready formats.
  • Data Preparation & Feature Engineering
    • Analyze and process structured/unstructured data for training and evaluation.
    • Develop feature extraction and selection pipelines to improve model performance.
  • Experimentation & Optimization
    • Run controlled experiments and perform statistical analysis to validate models.
    • Refine model hyperparameters and evaluation metrics for optimal performance.
  • Deployment & Integration
    • Work closely with ML Ops to deploy and monitor models in production environments.
    • Ensure all models are integrated seamlessly into existing systems.
  • Collaboration & Code Quality
    • Participate in code reviews, pair programming, and knowledge-sharing sessions.
    • Write testable, production-quality code that aligns with engineering best practices.
Qualifications & Skills
  • 3–5 years as an ML/AI Engineer or 1–3 years in an ML/AI leadership role
  • Proven experience building and deploying machine learning models in production
  • Solid understanding of classical ML algorithms (classification, regression, clustering)
  • Experience working with changing datasets and real-time data pipelines
  • Hands-on experience with Python and frameworks like PyTorch, TensorFlow, Scikit-learn
  • Strong knowledge of data processing (ETL), feature engineering, and statistical evaluation
  • Solid understanding of REST APIs, CI/CD, and containerized deployments (Docker, Kubernetes)
  • Strong communication, analytical thinking, and problem-solving skills
  • Bachelor's degree in Computer Science, Mathematics, Engineering, or a related quantitative field
Preferred Qualifications (Nice-to-Have)
  • Master's or PhD degree in Computer Science, Engineering, or a related field
  • Experience with neural networks and deep learning applications in computer vision, time-series analysis, or reinforcement learning
  • Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker, etc.)
  • Exposure to cloud platforms (AWS, GCP, Azure)
  • Familiarity with version control and experimentation tracking tools
  • Basic knowledge of data governance, security, and compliance standards

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