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Python Data Science Jobs in San Jose, CA (NOW HIRING)

Contribute to the continuous improvement of data science processes and methodologies. Technologies to be Used: * Python * SQL * Tableau * Power BI * TensorFlow * PyTorch * Various data sources ...

Data Science Engineer

San Jose, CA · On-site

$134K - $161K/yr

Proven hands - on experience in Python/PySpark/Scala and ability to manipulate data using Pandas ... scientists and machine learning engineers daily. Nice to have * Showcase your work if you are an ...

... data science, analytics, or a related quantitative role, with a track record of independently ... of Python or R • Experience in product analytics, experimentation, A/B testing, and causal ...

Data Scientist

San Ramon, CA · On-site

$93 - $98/hr

Strong command of languages like Python, R, and SQL for data manipulation and model development ... Provides hands-on execution and implementation of data science models. * Translates business ...

Principal Data Scientist

Oakland, CA · On-site

$128 - $148/hr

Master's Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical ... Proficiency with Python or PySpark, code reviews, and code development best practices.

Data Scientist

San Francisco, CA · On-site

$150K - $185K/yr

... data science experience - hands-on, delivery-focused, and measurable in shipped models and production systems * Expert-level Python - clean, modular, testable, production-ready code is your standard ...

... data science experience -- hands-on, delivery-focused, and measurable in shipped models and production systems * Expert-level Python -- clean, modular, testable, production-ready code is your ...

... data science experience - hands-on, delivery-focused, and measurable in shipped models and production systems * Expert-level Python - clean, modular, testable, production-ready code is your standard ...

MSAT Data Science Engineer

Newark, CA · On-site

$120K - $140K/yr

We are seeking a highly motivated individual to join us as a Data Science Engineer, Manufacturing ... Python and R and data analytics tools, including JMP, Spotfire, Tableau, R-Studio · Knowledge of ...

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Python Data Science information

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How much do python data science jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for python data science in San Jose, CA is $68.70, according to ZipRecruiter salary data. Most workers in this role earn between $56.63 and $78.03 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Python Data Science position, and why are they important?

To thrive in Python Data Science, you need strong programming skills in Python, a solid understanding of statistics, data manipulation, and experience with data analytics or machine learning, often supported by a bachelor’s or master’s degree in a quantitative field. Familiarity with tools such as pandas, NumPy, scikit-learn, Jupyter Notebooks, and knowledge of SQL are typically essential; certifications like Google Data Analytics or IBM Data Science can be advantageous. Critical thinking, problem-solving, and effective communication are key soft skills for translating data insights into actionable business recommendations. These skills are crucial to efficiently analyze large datasets, build predictive models, and deliver meaningful insights that drive decision-making.

How much does a Python data scientist make?

A Python data scientist's salary typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals with strong skills in machine learning, statistical analysis, and data visualization tools like Pandas and TensorFlow tend to earn higher salaries.

What are typical day-to-day responsibilities in a Python Data Science role?

In a Python Data Science role, your typical day might involve collecting, cleaning, and preparing raw data, exploring datasets to uncover patterns and trends, and building or evaluating predictive models. You’ll regularly use Python libraries to conduct analyses, visualize results, and collaborate with cross-functional teams such as product managers or engineers to define business objectives. Presenting your findings in clear, actionable formats for both technical and non-technical stakeholders is also a key part of the job. This dynamic environment emphasizes continuous learning, problem-solving, and close communication with other departments to align analytical insights with organizational goals.

Is Python useful in data science?

Python is a fundamental tool for data scientists, including those in data science roles, due to its extensive libraries such as Pandas, NumPy, and scikit-learn that facilitate data analysis, visualization, and machine learning. Its simplicity and versatility make it a preferred programming language in the data science field, often complemented by knowledge of SQL and data visualization tools.

What is a Python Data Science job?

A Python Data Science job involves using Python to analyze, process, and visualize data to extract insights and inform decision-making. It typically includes working with libraries like Pandas, NumPy, and Scikit-learn for data manipulation, statistical analysis, and machine learning. Professionals in this role may clean and preprocess data, build models, and communicate findings through reports or visualizations. Python Data Scientists often work in industries like finance, healthcare, and technology to solve complex problems and optimize business strategies.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into data science at various ages. Success depends on acquiring relevant skills such as programming in Python, understanding statistics, and working with tools like Jupyter notebooks, regardless of age.

Is Python a high paying job?

Python Data Science roles are generally well-paid due to high demand for skills in data analysis, machine learning, and automation. Salaries vary based on experience, location, and industry, but professionals with Python expertise often earn above average wages in the tech sector.
What are the most commonly searched types of Python Data Science jobs in San Jose, CA? The most popular types of Python Data Science jobs in San Jose, CA are:
What are popular job titles related to Python Data Science jobs in San Jose, CA? For Python Data Science jobs in San Jose, CA, the most frequently searched job titles are:
What cities near San Jose, CA are hiring for Python Data Science jobs? Cities near San Jose, CA with the most Python Data Science job openings:

Data Scientist

MhyMatch

San Francisco, CA • On-site, Remote

Full-time

Medical, Retirement, PTO

Posted 13 days ago


Job description

Location: Bangalore, San Francisco (US)

Mode of Work: Remote/Hybrid

Brief Overview of the Job Description:
Our Client is seeking a highly skilled Data Scientist to leverage large volumes of data using modern tools and technologies to uncover insights, build predictive models, and contribute to strategic decision-making. This role requires a blend of technical data science expertise, analytical problem solving, and a passion for transforming data into actionable insights.

Key Responsibilities:

  • Design and implement statistical models and machine learning algorithms to analyze diverse sources of data and achieve targeted outcomes.
  • Lead data mining and collection strategies to improve data reliability, efficiency, and quality.
  • Collaborate with cross-functional teams to understand business needs and provide data-driven solutions.
  • Continuously evaluate and identify new technologies, tools, and data sets to enhance the analytics capabilities of the organization.
  • Present findings to stakeholders, translating complex data insights into understandable business decisions.
  • Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity.
  • Ensure data accuracy and integrity by performing thorough testing and validation.
  • Apply statistical and machine learning techniques to solve complex business problems.
  • Create visualizations and dashboards to monitor and report on key metrics and trends.
  • Participate in code reviews to ensure code quality and adherence to best practices.
  • Mentor junior data scientists and provide technical guidance.
  • Contribute to the continuous improvement of data science processes and methodologies.


Technologies to be Used:

  • Python

  • SQL

  • Tableau

  • Power BI

  • TensorFlow

  • PyTorch

  • Various data sources (structured and unstructured)

Qualifications:

  • Masters degree or Ph.D. in Data Science, Computer Science, Statistics, or a closely related field.
  • Certifications in relevant technologies and frameworks are advantageous.
  • Minimum 4 years of relevant experience

Knowledge:

Expert understanding of data science, machine learning, AI, and advanced analytics techniques.

Skills:

  • Advanced proficiency in Python and R for statistical programming and model development.
  • Strong experience with SQL and database management systems.
  • Skilled in data visualization tools such as Tableau or Power BI to convey insights visually.
  • In-depth knowledge of machine learning frameworks like TensorFlow or PyTorch.
  • Ability to work with both structured and unstructured data from various sources.

Attitude:

  • Analytical and critical thinker with meticulous attention to detail.

  • Ability to work in a dynamic environment and adapt to evolving business needs.

  • Strong communication skills with the ability to explain complex solutions to non-technical stakeholders.

  • Team player who is also capable of working independently.

Work Environment:

  • A collaborative and innovative workplace focused on leveraging data to solve complex business challenges.
  • Supportive team culture promoting continuous professional development and growth.

Key Performance Indicators:

  • Accuracy and performance of statistical models and machine learning algorithms.
  • Efficiency and reliability of data mining and collection strategies.
  • Impact of data-driven solutions on business outcomes.
  • Adoption and integration of new technologies and data sets.
  • Effectiveness of data presentations and stakeholder communications.
  • Quality and scalability of data pipelines and API integrations.
  • Accuracy and integrity of data maintained through testing and validation.
  • Innovation in applying statistical and machine learning techniques.
  • Utility and usability of visualizations and dashboards created.
  • Code quality and adherence to best practices through code reviews.
  • Guidance and development provided to junior data scientists.
  • Continuous improvement of data science processes and methodologies.


Salary and Benefits:

  • Competitive salary package with performance bonuses.

  • Health insurance, retirement plans, and paid time off.

  • Opportunities for continuous learning and professional development through workshops, courses, and conferences.

  • Flexible working hours and potential for remote work arrangements.

Company Overview:
Our client is a leading product-based software company, dedicated to creating innovative and efficient solutions that address complex business challenges. Their suite of products enhances operational efficiencies and drives digital transformation, empowering businesses to achieve sustainable growth and competitive advantage. The company is committed to creating a diverse environment and is proud to be an equal opportunity employer, encouraging applications from all backgrounds and cultures.

Diversity Policy:

We are committed to creating a diverse environment and proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Career Growth:

Clear pathways for career advancement in a supportive environment aimed at fostering professional growth and exploration of new technologies in the field of data science.