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Predictive Modeling Jobs in California (NOW HIRING)

Power Integrations

Device Modeling Engineer

San Jose, CA · On-site

$120 - $150/hr

Support development of next-generation GaN and high-voltage technologies through predictive modeling * Characterization & Parameter Extraction * Define and execute device characterization plans for ...

Golden State

Data Scientist

San Francisco, CA · Remote

$165K/yr

In this role, you will make a positive impact on our research, predictive modeling, and long-term decision making to support our Basketball Operations stakeholders. Additionally, you will work ...

AEG

Data Scientist

San Francisco, CA · On-site

$165K/yr

In this role, you will make a positive impact on our research, predictive modeling, and long-term decision making to support our Basketball Operations stakeholders. Additionally, you will work ...

LMI

Data Scientist - Clearance Required

Fort Bragg, CA · On-site

Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%. * Apply statistical analysis, feature engineering, time ...

LMI

Data Scientist - Clearance Required

Fort Bragg, CA · On-site

Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%. * Apply statistical analysis, feature engineering, time ...

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All JobsPredictive Modeling JobsPredictive Modeling Jobs in California

Predictive Modeling information

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How much do predictive modeling jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for predictive modeling in California is $57.94, according to ZipRecruiter salary data. Most workers in this role earn between $51.97 and $67.36 per hour, depending on experience, location, and employer.

What is predictive modeling?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What are the key skills and qualifications needed to thrive in predictive modeling, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What are the most commonly searched types of Predictive Modeling jobs in California?

The most popular types of Predictive Modeling jobs in California are:

What are popular job titles related to Predictive Modeling jobs in California?

For Predictive Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Predictive Modeling jobs in California look for?

The top searched job categories for Predictive Modeling jobs in California are:

What cities in California are hiring for Predictive Modeling jobs?

Cities in California with the most Predictive Modeling job openings:

Predictive Modeling jobs near you
Infographic showing various Predictive Modeling job openings in California as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $120,524 per year, or $57.9 per hour.

Job Title: Data Scientist - Contract jobs - San Jose, CA

Tech Mirrors

San Jose, CA • On-site

$130 - $195/hr

Other

Posted 6 days ago

Job description

Job Title: Data Scientist - 10+yrs-

San Jose, United States - onsite

client - Virtusa

Need only H1

Job Summary

We are looking for an experienced Data Scientist with strong hands-on expertise in Python, SQL, Statistical Analysis, Machine Learning, and Predictive Modeling. The candidate will work on end-to-end data science projects, from data preparation and feature engineering through model development, deployment, and performance monitoring.

Key Responsibilities

  • Develop predictive models and machine learning solutions using Python.
  • Perform statistical analysis and identify patterns and trends in data.
  • Work with structured and unstructured datasets.
  • Perform data cleaning, validation, transformation, and feature engineering.
  • Develop and optimize ML models using Scikit-learn, Pandas, and NumPy.
  • Deploy machine learning models into production.
  • Track experiments and maintain model documentation using MLflow, DVC, or Jupyter.
  • Ensure data quality, model accuracy, and performance.
  • Analyze results and translate technical findings into actionable business insights.
  • Work independently on projects from data discovery through deployment.
  • Collaborate with business and technical teams to solve data-driven problems.

Required Skills

  • Python - Mandatory
  • SQL - Mandatory
  • Data Science
  • Predictive Modeling
  • Statistical Analysis
  • Machine Learning
  • Scikit-learn
  • Pandas
  • NumPy
  • Feature Engineering
  • Data Integration
  • Model Deployment
  • Structured & Unstructured Data

Preferred Skills

  • MLflow
  • DVC
  • Jupyter
  • Model Monitoring
  • MLOps
  • Production Machine Learning
  • Data Visualization
  • Cloud platforms
  • Git

Primary Skills

  • Python | SQL | Data Science | Machine Learning | Predictive Modeling | Statistical Analysis | Scikit-learn | Pandas | NumPy

Secondary Skills

  • Feature Engineering | Data Integration | MLflow | DVC | Jupyter | Model Deployment | MLOps | Model Documentation

Ideal Candidate

The ideal candidate should have 4+ years of hands-on Data Science experience, with strong expertise in Python, SQL, predictive modeling, statistical analysis, and machine learning.

The candidate must be comfortable taking ML projects from data discovery and feature engineering through model development and production deployment.

Recruiter Screening - Must Have

Python + SQL + Machine Learning + Predictive Modeling + Statistical Analysis + Scikit-learn + Pandas/Num

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