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Phd Statistics Jobs in Riverside, CA (NOW HIRING)

AbbVie

AI Engineering Analyst (Hybrid)

Irvine, CA · On-site

Bachelor's or Master's degree in statistics, mathematics, analytics, bioinformatics, data science, computer science or equivalent field with 4+ years (BS), 2+ years (MS) or 1+ years (PhD) of related ...

Ingram Micro, Inc.

Senior Agentic AI Engineer

Irvine, CA · On-site

$170 - $230/hr

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Statistics, Machine Learning, or a related technical field. A PhD is a plus. * 7+ years of hands‑on experience in ...

AbbVie

AI Engineering Analyst (Hybrid)

Irvine, CA · On-site

$84K/yr

Bachelor's or Master's degree in statistics, mathematics, analytics, bioinformatics, data science, computer science or equivalent field with 4+ years (BS), 2+ years (MS) or 1+ years (PhD) of related ...

Masimo

Engineer II, Algorithm

Irvine, CA · On-site

$120K - $150K/yr

Apply statistical analysis, numerical modeling, machine learning, and digital signal processing ... Master's or PhD degree preferred. Language requirements: * Ability to read, write, and communicate ...

Masimo Corporation

Engineer II, Algorithm

Irvine, CA · On-site

$120 - $150/hr

Apply statistical analysis, numerical modeling, machine learning, and digital signal processing ... Master's or PhD degree preferred. Language requirements: * Ability to read, write, and communicate ...

Masimo

Engineer II, Algorithm

Irvine, CA · On-site

$120K - $150K/yr

Apply statistical analysis, numerical modeling, machine learning, and digital signal processing ... Master's or PhD degree preferred. Language requirements: * Ability to read, write, and communicate ...

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Showing results 21-40

All JobsPhd Statistics JobsPhd Statistics Jobs in Riverside, CA

Phd Statistics information

See Riverside, CA salary details

$23.7K

$93.7K

$173.6K

How much do phd statistics jobs pay per year?

As of Sep 5, 2026, the average yearly pay for phd statistics in Riverside, CA is $93,722.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,979.00 and $122,609.00 per year, depending on experience, location, and employer.

What is a PhD statistics?

A PhD Statistics job typically involves conducting advanced statistical research, developing new methodologies, and applying statistical techniques to solve complex problems in various fields such as healthcare, finance, or technology. Professionals in these roles may work in academia, government, or industry, analyzing data, designing experiments, and publishing findings. They often collaborate with interdisciplinary teams to extract insights from large datasets and improve decision-making processes.

What are the key skills and qualifications needed to thrive in a PhD statistics position?

To thrive as a PhD in Statistics, you need advanced knowledge of statistical theory, data analysis, and research methodologies, typically backed by a doctorate in statistics or a closely related field. Expertise with statistical software such as R, SAS, Python, or MATLAB, along with experience in data management systems, is crucial. Strong problem-solving abilities, clear communication, and the capacity to work both independently and as part of interdisciplinary teams are highly valued soft skills. These qualities enable you to devise rigorous solutions to complex data challenges, effectively collaborate with colleagues, and translate findings for stakeholders.

What are the typical projects or research areas for someone with a PhD in statistics?

A PhD in Statistics often works on projects involving the design and analysis of experiments, predictive modeling, advanced data analytics, and the development of new statistical methodologies. Depending on the industry, these may span sectors like healthcare, finance, technology, or government, requiring collaboration with diverse teams of subject matter experts. The role may also involve publishing research, presenting findings, and supporting organizational decision-making with evidence-based insights. This dynamic environment allows statisticians to solve real-world problems and continuously learn new analytical techniques.

How much does a PhD statistician make?

A PhD statistician typically earns between $80,000 and $150,000 annually, depending on experience, industry, and location. Senior roles or positions in finance, technology, or healthcare can offer higher salaries, especially with specialized skills in statistical programming and data analysis tools.

Is a PhD in statistics worth it?

A PhD in statistics can lead to advanced roles in research, data analysis, and academia, often requiring strong analytical and programming skills in tools like R or Python. While it offers high-level expertise and potential for higher salaries, it also involves significant time and financial investment, and job prospects depend on industry demand and individual specialization.

What can I do with a PhD in statistics?

A PhD in statistics prepares individuals for advanced roles in data analysis, research, and modeling across industries such as healthcare, finance, technology, and government. Graduates often work as data scientists, quantitative analysts, research scientists, or statisticians, utilizing skills in statistical software, programming, and data interpretation. These roles typically require strong analytical abilities and knowledge of statistical methods and tools like R, Python, or SAS.

What are the most commonly searched types of Phd Statistics jobs in Riverside, CA?

The most popular types of Phd Statistics jobs in Riverside, CA are:

What are popular job titles related to Phd Statistics jobs in Riverside, CA?

For Phd Statistics jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Phd Statistics jobs in Riverside, CA look for?

The top searched job categories for Phd Statistics jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Phd Statistics jobs?

Cities near Riverside, CA with the most Phd Statistics job openings:

Phd Statistics jobs near you
Infographic showing various Phd Statistics job openings in Riverside, CA as of August 2026, with employment types broken down into 77% Full Time, 21% Part Time, and 2% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $93,722 per year, or $45.1 per hour.

Computer Vision Engineer - 3D

Stark Pharma Solutions Inc

Irvine, CA • On-site

$119K - $141K/yr

Contractor

Re-posted 28 days ago

Job description

Hi,

My name is Karthik Mutyala, and I am a Recruitment Manager with Stark Pharma Solutions, specializing in opportunities across the Pharmaceutical, Biotechnology, Medical Device, and Life Sciences industries.

I am actively connecting with professionals for current and upcoming opportunities. If you are open to exploring new roles or would like to stay informed about relevant positions, please send me your updated resume along with the best number and time to reach you.

Role: 3D Data Scientist / Computer Vision Engineer

Location: Irvine, CA (Hybrid)

Duration: 12-Month Contract

Schedule: Monday – Friday | 8:00 AM – 5:00 PM PST

Position Overview

We are seeking a highly skilled 3D Data Scientist / Computer Vision Engineer to support the development and validation of advanced 3D imaging technologies within a cutting-edge digital health and aesthetics environment. This role will focus on validating 3D facial capture systems, developing novel 3D digital biomarkers, and applying machine learning techniques to complex 3D datasets.

The ideal candidate combines expertise in data science, computer vision, machine learning, and 3D modeling technologies, with the ability to translate complex data into clinically meaningful insights.

Key Responsibilities

3D Imaging & Validation

  • Lead validation activities for 3D facial capture and imaging systems.
  • Design and execute validation studies to evaluate accuracy, reproducibility, and performance across diverse datasets.
  • Develop quantitative testing methodologies and statistical frameworks to assess 3D image quality and geometric precision.
  • Document findings and communicate results to technical and business stakeholders.
  • Computer Vision & Digital Endpoint Development
  • Develop and validate novel 3D digital measurements and biomarkers from facial imaging data.
  • Create scalable workflows for processing, analyzing, and extracting features from 3D meshes, point clouds, and photogrammetry data.
  • Support the development of clinically relevant outcome measures using advanced image analysis techniques.
  • Establish best practices for data preprocessing, quality control, and feature engineering.
  • Machine Learning & Data Science
  • Build, train, and evaluate machine learning models using 3D imaging datasets.
  • Apply computer vision, geometric deep learning, and statistical modeling techniques to solve complex analytical challenges.
  • Benchmark model performance and optimize algorithms for robustness, accuracy, and scalability.
  • Collaborate with software, engineering, and scientific teams to deploy and improve analytical solutions.
  • Cross-Functional Collaboration
  • Partner with imaging specialists, software engineers, clinicians, and product teams to define technical requirements and project goals.
  • Support research initiatives and contribute to innovation in digital health, imaging, and computer vision technologies.
  • Stay current with emerging trends in AI, machine learning, computer vision, and 3D data science.

Required Qualifications

  • Bachelor's, Master's, or PhD in Computer Science, Data Science, Computer Vision, Biomedical Engineering, Machine Learning, or a related quantitative field.
  • 3+ years of experience in Data Science, Machine Learning, Computer Vision, or related technical roles.
  • Strong proficiency in Python and data science frameworks such as NumPy, Pandas, SciPy, Scikit-learn, PyTorch, or TensorFlow.
  • Hands-on experience working with:
  • 3D Meshes
  • Point Clouds
  • Depth Maps
  • Photogrammetry Data
  • Experience with 3D visualization, rendering, or modeling tools such as Blender, Autodesk Maya, or similar platforms.
  • Strong background in statistical analysis, validation methodologies, and experimental design.
  • Excellent communication and technical documentation skills.