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Python Data Science Jobs in Irvine, CA (NOW HIRING)

Saransh Inc

AI/ML Architect

Irvine, CA · On-site

$68.50 - $88/hr

AI/ML, Data Science, AI Architecture, Python, LLM, CI/CD Must Have Skills: • Python & Backend Development • LLM / Generative AI Application Development • Agent-Based AI Systems • RAG / Vector ...

omega solutions, Inc.

Sr. Data Scientist

Santa Ana, CA · On-site

Sr. Data Scientist Santa Ana, CA 6 months : What is the specific title of the position? Senior Data ... SQL, Python, Spark, Hive Libraries: Scikit-Learn, Numpy Analytics: Regression, Classification ...

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site +1

$144K - $194K/yr

Partner with the Data Science team to architect intelligent routing logic that leverages Small ... Expert Python/FastAPI Developer: Proven experience in designing, scaling, and maintaining existing ...

Cotality

Principal Software Engineer (Python)

Irvine, CA · On-site

$144K - $194K/yr

Partner with the Data Science team to architect intelligent routing logic that leverages Small ... Expert Python/FastAPI Developer: Proven experience in designing, scaling, and maintaining existing ...

Pacificlife

MRM Senior Data Scientist

Newport Beach, CA · On-site

Bachelor's degree in statistics, data science, computer science, engineering, mathematics, or a ... Highly proficient in Python, ML libraries such as scikit-learn and data query language such as SQL ...

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How much do python data science jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for python data science in Irvine, CA is $62.92, according to ZipRecruiter salary data. Most workers in this role earn between $51.88 and $71.49 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.

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.

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.

What does a data scientist do with Python?

A data scientist uses Python to analyze and interpret large datasets, develop machine learning models, and create data visualizations. They utilize libraries like pandas, scikit-learn, and matplotlib to extract insights and support data-driven decision-making.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into data science later in their careers. 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 programming. Salaries vary based on experience, location, and industry, but professionals with Python expertise often earn above average wages in the tech sector.

How much do Python data scientists make?

Python data scientists typically earn a median salary ranging from $90,000 to $130,000 annually, depending on experience, location, and industry. Professionals with advanced skills in machine learning, statistical analysis, and data visualization tools like Pandas and TensorFlow tend to command higher salaries.
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Python Data Science jobs near you
Tech Lead - Data Scientist

Tech Lead - Data Scientist

Obsidian Security

Newport Beach, CA • On-site

Other

Posted 18 days ago

Job description

Tech Lead - Data ScientistAbout the Role

We are looking for a Technical Lead to drive the development of Obsidian's core ontology that powers our groundbreaking unified security config analysis, AI security, and threat detection product.

  • Scale this ontology as part of a team of 3-6 software engineers and data scientists to cover hundreds or thousands more enterprise application platforms. Drive automation of repeatable R&D subtasks.
  • Become an expert on foundational identity, authentication, authorization, network, and data security concepts. An unhealthy dose of curiosity about the design and administration - technology, people, and process - of complex application platforms such as GitHub, Salesforce, and Workday is a must. You will love exploring rabbit holes into esoteric domain knowledge related to these topics.
  • Formulate security problems as data and ML problems, constantly addressing and refining the customer outcome in collaboration with top-flight security teams from Global 1000 companies.
What We're Looking For
  • 6+ years of experience in data science, machine learning, or applied research, preferably with 2+ years in a technical leadership role.
  • A track record of shipping production ML or data systems at scale - ideally systems involving ontologies, knowledge graphs, entity resolution, or semantics over heterogeneous data sources.
  • Expert-level proficiency in Python and modern ML/data tooling.
  • Working knowledge of core security domains, or a strong ability to learn.
  • Experience formulating fuzzy business or security problems as concrete ML/data problems:
    • able to decompose ambiguous, ambitious problems into well-scoped subproblems and design experiments with statistical rigor.
    • comfortable being scrappy and diving deep into vendor documentation, APIs, and audit logs to find the necessary data sources
  • Excellent written and verbal communication skills; ability to engage credibly with technical security practitioners at large enterprises.

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