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Python Data Science Jobs in Los Angeles, CA (NOW HIRING)

Heluna Health

Data Scientist Supervisor

Alhambra, CA

$9.8K - $13K/mo

Quality Assurance & Best Practices - Establish and enforce best practices in data science ... Advanced programming skills in Python, R, and SQL for model development and data processing.

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

Quality Assurance & Best Practices - Establish and enforce best practices in data science ... Advanced programming skills in Python, R, and SQL for model development and data processing.

Fanatics Collectibles

Data Scientist

Los Angeles, CA · On-site

... data science, analytics, or a related quantitative role. * Working knowledge of SQL and experience querying large datasets. * Proficiency in Python or R for data analysis. * Foundational ...

Oscar Health

Data Scientist II

Los Angeles, CA · Hybrid

$131K - $172K/yr

... science, applied analytics, or a related quantitative field (industry, academia, or both) * 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data * 2+ years of ...

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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 Los Angeles, CA is $61.83, according to ZipRecruiter salary data. Most workers in this role earn between $50.96 and $70.24 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 Los Angeles, CA? The most popular types of Python Data Science jobs in Los Angeles, CA are:
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Python Data Science jobs near you
Research Associate Data Scientist

Research Associate Data Scientist

Cedars Sinai

Los Angeles, CA • On-site

$97K - $133K/yr

Full-time

Posted 23 days ago

Cedars-Sinai rating

8.6

Company rating: 8.6 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

37th of 1,020 rated hospitals

Job description


Research Associate Data Scientist (Cedars-Sinai Medical Center; Los Angeles, CA): Assist with the development, evaluation, and application of computational and statistical methods, including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data. Assist with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications. Create database-to-deployment pipelines for models using the necessary programming languages (primarily Python, R, and C++). Create sustainable data science infrastructure and adheres to data analysis/machine learning best practices. Perform exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods. Work with senior or lead data scientists, research programmers, and principal investigators to identify areas where data science can best be applied to answer biomedical research questions. Test and validate code to ensure robustness of data applications. Perform all other duties as assigned. Participate in the development of innovative algorithms and analytical methods. Participate in the evaluation and interpretation of all analytical methods and results. Participate in the oral and written communication of scientific results including publications.
Minimum requirements: Master's degree or foreign equivalent in Electrical Engineering, Computer Science, Machine Learning, Applied Mathematics, Biomedical Imaging, or related field, plus three (3) years of experience as a Research Associate Data Scientist, Computer Engineer, Biomedical Data Scientist, or related occupation.
Must have experience with the following: Python, C++, and R; developing, testing, validating, and optimizing production-level, version-controlled code (GitHub/GitLab and Azure DevOps) for algorithm development, statistical analysis, and deployment; implementing supervised and unsupervised learning algorithms (random forests, support vector machines, clustering, deep learning), with hands-on expertise training, fine-tuning, and deploying deep learning models using frameworks (PyTorch and TensorFlow), and adapting these methods to biomedical research problems; building end-to-end database-to-deployment pipelines including querying large relational databases (SQL), data cleaning, model training, validation, and deploying models in multiple computing environments; communicating scientific results effectively through peer-reviewed publications, patents, conference presentations, and internal technical reports; working with medical imaging data, including familiarity with industry-standard imaging formats (DICOM), image preprocessing workflows (segmentation, denoising, registration, resampling, and normalization), and use of imaging software libraries (SimpleITK, MONAI, or NiBabel) to prepare data for machine learning analysis; managing, processing, and optimizing large-scale 3D and 4D time-series datasets for deep learning model development on High-Performance Computing (HPC) or cloud-based GPU clusters.
Salary: $97,510 - $133,100 per year
To Apply: Any interested applicant may click on the APPLY NOW button above to apply for this position.
Job Req ID:18558
Responsibilities
  • Assists with the development, evaluation, and/or application of computational and statistical methods including artificial intelligence and machine learning algorithms and software for the analysis of biomedical data.
  • Assists with the presentation and communication of scientific results through laboratory meetings, scientific conferences, and peer-reviewed publications.
  • Creates database-to-deployment pipelines for models using the necessary programming languages (primarily R, Python, SQL, neo4j).
  • Creates sustainable data science infrastructure and adheres to data analysis/machine learning best practices.
  • Performs data cleaning, quality control, and exploratory data analysis to gauge the need for or appropriateness of advanced analytical methods
  • Assists research, senior research, and/or lead research data scientists and principal investigators to identify areas where data science can best be applied to answer biomedical research questions.
  • Tests and validates code to ensure robustness of data applications with version control through GitHub.

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