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Hourly Python Data Science Jobs in Santa Clara, CA

Unikon IT

Data Scientist

San Jose, CA · On-site

Python - Data Science Preferred Qualifications * Hands-on experience with major cloud platforms (AWS, Google Cloud, Azure) and data lakes. * Familiarity with version control using Git. * Knowledge of ...

Five9

Vice President, Data Science

San Ramon, CA · On-site

The data science team is very much applied - their work directly makes its way into real products ... Ability to work with engineering teams using modern software practices (Python, data platforms ...

Info Way Solutions

Data Science

Fremont, CA · On-site

Info Way Solutions is seeking a Data Science professional to join their team. The role involves ... Python, Scala, Java, C++, etc. • Experience supporting and working with cross-functional teams in ...

Info Way Solutions

Data science engineer

Fremont, CA · On-site

$125K - $151K/yr

Info Way Solutions is seeking a talented Data Science Engineer to join their team. The role ... sources. • Utilize Python and Spark for data preprocessing, feature engineering, and model ...

Info Way Solutions

Data Science Engineer

Fremont, CA · On-site

$125K - $151K/yr

Info Way Solutions is seeking a talented Data Science Engineer to join their team. The role ... sources. • Utilize Python and Spark for data preprocessing, feature engineering, and model ...

1872 Consulting

Data Science Manager

Santa Clara, CA · On-site

... Python • Solid understanding of Machine Learning algorithms and Natural Language Processing ... data • Experience with Java • Advanced degree in Computational Linguistics, or Computer Science ...

Tapestry

Data Science Manager

Mountain View, CA · On-site

Data Scientists work across the organization to help shape our business and technical strategies by ... Experience in Python, SQL, R, Pandas, Scikit-Learn, other ML frameworks as appropriate.

Tapestry

Data Science Manager

Mountain View, CA · On-site

Data Scientists work across the organization to help shape our business and technical strategies by ... Experience in Python, SQL, R, Pandas, Scikit-Learn, other ML frameworks as appropriate.

LLNL

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems.

LLNL

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems. * Intermediate ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$134K - $161K/yr

Broad experience with Python programming and software development. * Comprehensive experience applying machine learning, deep learning, or data science methods to real-world problems. * Intermediate ...

Match Point Solutions

Data Scientist

Pleasanton, CA · Remote

$75 - $80/hr

Developing computer vision models that improve, accelerate, and automate asset inspections processes Strong Python programing Department Overview The Data Science & Artificial Intelligence Department ...

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Hourly Python Data Science information

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How much do hourly python data science jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for hourly python data science in Santa Clara, CA is $68.85, according to ZipRecruiter salary data. Most workers in this role earn between $56.73 and $78.22 per hour, depending on experience, location, and employer.

What is an hourly Python data science job?

Hourly Python Data Science jobs are roles where professionals use Python programming to analyze, interpret, and visualize data, and are paid based on the number of hours they work. These positions often involve tasks such as data cleaning, statistical analysis, machine learning, and data visualization. Hourly data science jobs offer flexibility for both employers and workers, making them popular for freelance, contract, or part-time arrangements. Python's robust libraries and tools make it a preferred language for these roles.

What are the key skills and qualifications needed to thrive as an hourly Python data science professional?

To thrive as an Hourly Python Data Science professional, you need a solid understanding of statistics, data analysis, and programming in Python, often supported by a degree in a quantitative field or equivalent experience. Familiarity with tools like Pandas, NumPy, scikit-learn, and data visualization libraries, as well as experience with version control systems like Git, is typically required. Strong problem-solving abilities, effective communication, and adaptability help you deliver insights and solutions to clients efficiently. These skills ensure accurate analysis, clear reporting, and the ability to meet diverse project needs in a flexible, project-based environment.

What are some common challenges faced by hourly Python data science professionals, and how can they be addressed?

Hourly Python Data Science professionals often encounter challenges such as managing multiple clients with varying expectations, adapting quickly to different data environments, and handling inconsistent workloads. To address these, it's important to establish clear communication with clients about project scope and deadlines, maintain well-organized code and documentation for easy context switching, and utilize tools like version control and virtual environments. Building a strong personal workflow and prioritizing time management can help ensure high-quality deliverables across diverse projects.

What is the difference between Hourly Python Data Science vs Data Analyst?

AspectHourly Python Data ScienceData Analyst
Required SkillsPython, statistical analysis, machine learningExcel, SQL, data visualization
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Common CertificationsPython certifications, data science coursesExcel, Tableau, SQL certifications

Hourly Python Data Science roles focus on advanced analytics, machine learning, and programming with Python, often in tech-driven environments. Data Analysts typically handle data cleaning, visualization, and reporting using tools like Excel and SQL. While both roles require data handling skills, Python Data Science positions demand programming expertise and statistical knowledge, making them more technical and specialized.

What are the most commonly searched types of Python Data Science jobs in Santa Clara, CA?

The most popular types of Python Data Science jobs in Santa Clara, CA are:

Hourly Python Data Science jobs near you
Infographic showing various Hourly Python Data Science job openings in Santa Clara, CA as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $143,202 per year, or $68.8 per hour.

Data Scientist

San Jose, CA • On-site

Unikon IT
IT Services • 11 - 50 employees
Learn more about Unikon ITexternal

Other

Posted 14 days ago

Job description

Data Scientist

Location : San Jose , CA (Hybrid)

Description:

analyzes large, complex datasets to derive actionable insights, design machine learning algorithms, and build robust predictive models. This role involves collaborating closely with product, engineering, and business leaders to turn raw data into strategic, scalable solutions that drive company growth and efficiency. The ideal candidate will blend strong programming and statistical expertise with advanced AI capabilities while strictly adhering to data privacy, ethical guidelines, and organizational standards.

Key Responsibilities

Data Engineering & Infrastructure

  • Build and maintain ETL processes to clean, transform, and merge structured and unstructured data from multiple sources.
  • Optimize data infrastructure for performance, scalability, and cost-efficiency.
  • Automate routine data tasks and workflows to enhance overall operational efficiency.

Advanced Analytics & Modeling

  • Conduct statistical analysis and data mining on large datasets to identify historical trends, patterns, and anomalies.
  • Design, implement, and deploy statistical models, machine learning algorithms, and forecasting systems.
  • Drive the design, development, and optimization of end-to-end AI/ML frameworks, integrating Natural Language Processing (NLP) techniques where applicable.
  • Design and execute controlled A/B tests to evaluate new features or business strategies.

Collaboration & Communication

  • Partner with cross-functional teams to translate complex technical findings into clear, plain-English recommendations.
  • Create automated dashboards and visual stories to track performance using modern business intelligence tools.
  • Adhere to internal standards, security policies, responsible AI practices, and ethical data privacy guidelines.

Required Skills & Qualifications

Technical Skills & Tools

  • Strong proficiency in Python (including Pandas, NumPy, Scikit-Learn, TensorFlow) or R.
  • Practical experience with distributed storage and processing frameworks like PySpark, Apache Spark, Hadoop, Hive, Snowflake, or Azure Databricks.
  • Advanced knowledge of SQL for complex querying and data extraction.
  • Solid understanding of core machine learning (regression, classification, clustering, decision-making trees) and NLP techniques.
  • Firm grasp of statistical analysis, probability distributions, and hypothesis testing.
  • : Experience with tools such as Tableau, Power BI, and Matplotlib.

Core Mandatory Skills

  • PySpark - Data Science
  • Python - Data Science

Preferred Qualifications

  • Hands-on experience with major cloud platforms (AWS, Google Cloud, Azure) and data lakes.
  • Familiarity with version control using Git.
  • Knowledge of prompt engineering, generative AI tools, and productivity automation.

Desired Attributes

  • Natural curiosity coupled with strong analytical abilities to tackle real-world data projects.
  • Ability to explain complex model mechanics to non-technical stakeholders and executives.
  •  Adaptability to rapidly evolving AI technologies and a commitment to staying updated on model interpretability.

Apply