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Scientist Python Jobs in Walnut, CA (NOW HIRING)

YO AI Labs

Data Scientist

Glendale, CA · On-site

Python Machine Learning, data science, AWS, Statistical Modeling, Semantic Search, Vector DB, GenAI, SQL Qualifications: * Bachelors in Statistics, Economics, Computer Science, Engineering ...

BeeGenius

Data Scientist

Los Angeles, CA · On-site

D. in Computer Science, Statistics, or a related field • Proficiency in programming languages such as Python or R • Experience with machine learning algorithms and statistical modeling techniques ...

Panasonic

Data Scientist IV

Irvine, CA · On-site

Strong hands-on Python and SQL skills for data science (pandas, scikit-learn, and similar). * Should be strong in AWS suite, experience working with AWS Cloud or similar environments and tools for ...

YO AI Labs

Data Scientist

Glendale, CA · On-site

Python Machine Learning, data science, AWS, Statistical Modeling, Semantic Search, Vector DB, GenAI, SQL Technical Responsibilities : * Design and Execute Experiments: Lead end-to-end A/B testing ...

VCA Animal Hospitals

Data Scientist

Los Angeles, CA

$107K - $161K/yr

The Data Scientist is a key member of the Pricing Strategy & Insights team, responsible for ... Prepare and transform largescale datasets using SQL and Python/R; partner with data engineering and ...

Boot Barn

Data Scientist

Irvine, CA · On-site

$95K - $120K/yr

DATA SCIENTIST REPORTS TO: DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where ... Develop high-quality, modular Python code for model training and experimentation using libraries ...

Boot Barn

Data Scientist

Irvine, CA · On-site

$95K - $120K/yr

DATA SCIENTIST REPORTS TO: DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where ... Develop high-quality, modular Python code for model training and experimentation using libraries ...

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Scientist Python information

See Walnut, CA salary details

$38.2K

$125.1K

$200.2K

How much do scientist python jobs pay per year?

As of Sep 6, 2026, the average yearly pay for scientist python in Walnut, CA is $125,077.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $138,600.00 per year, depending on experience, location, and employer.

What does a Scientist Python do?

A Scientist Python, often referred to as a Python Scientist or Data Scientist specializing in Python, uses the Python programming language to analyze data, build predictive models, and solve scientific or business problems. They work with large datasets, apply statistical and machine learning techniques, and create visualizations to interpret results. Their work often involves writing code to clean, manipulate, and analyze data efficiently. Python's extensive libraries, such as Pandas, NumPy, and SciPy, make it a popular choice for scientific computing and data science tasks.

What are the key skills and qualifications needed to thrive as a Scientist Python?

To thrive as a Scientist Python, you need strong programming skills in Python, a solid background in scientific methods or data analysis, and typically an advanced degree in a relevant field such as computer science, physics, or biology. Experience with data analysis libraries (e.g., NumPy, pandas, SciPy), machine learning frameworks (e.g., scikit-learn, TensorFlow), and version control systems is commonly required. Critical thinking, effective communication, and problem-solving abilities help distinguish top performers in this role. These skills enable efficient data-driven research, reproducible scientific workflows, and successful collaboration in multidisciplinary environments.

How does a Scientist Python typically collaborate with other team members during research and development projects?

Scientist Python professionals frequently work in multidisciplinary teams, collaborating closely with data scientists, domain experts, and software engineers. They are often responsible for developing and implementing Python-based models or algorithms, then integrating their work with broader research goals or product pipelines. Regular communication, code reviews, and shared documentation are common practices to ensure alignment and reproducibility. This collaborative environment offers opportunities to learn from peers and contribute to diverse projects, fostering both technical and professional growth.

What is the difference between Scientist Python vs Data Analyst Python?

AspectScientist PythonData Analyst Python
Required CredentialsBachelor's or Master's in Science, Data Science, or related fields; Python proficiencyBachelor's in Statistics, Data Analysis, or related fields; Python skills
Work EnvironmentResearch labs, R&D departments, tech companiesBusiness intelligence teams, marketing, finance departments
Employer & Industry UsageResearch institutions, tech firms, healthcareCorporate, finance, retail, marketing
Common Search & ComparisonYesYes

Scientist Python and Data Analyst Python roles share similar skills like Python programming and data handling. However, Scientists typically focus on research, experimentation, and developing new models, often working in research-heavy environments. Data Analysts concentrate on interpreting existing data to inform business decisions, working mainly in corporate settings. Both roles require strong analytical skills and Python expertise, but their focus and work environments differ significantly.

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. Advanced skills in machine learning, data analysis, and proficiency with tools like Pandas and TensorFlow can lead to higher compensation.

What are 10 careers related to Python?

A Python-focused scientist can pursue careers such as data scientist, machine learning engineer, data analyst, software developer, automation engineer, research scientist, bioinformatics specialist, quantitative analyst, AI engineer, and backend developer. These roles often require strong programming skills, knowledge of libraries like NumPy and Pandas, and experience with data analysis or software development environments.

Which scientist Python job is in demand?

Data scientist and machine learning engineer roles that require Python skills are currently in high demand across industries. These positions often seek proficiency in libraries like Pandas, NumPy, and TensorFlow, and may require experience with data analysis, modeling, and cloud platforms. Strong programming skills and relevant certifications can improve job prospects in this field.

What are popular job titles related to Scientist Python jobs in Walnut, CA?

For Scientist Python jobs in Walnut, CA, the most frequently searched job titles are:

What job categories do people searching Scientist Python jobs in Walnut, CA look for?

The top searched job categories for Scientist Python jobs in Walnut, CA are:

What cities near Walnut, CA are hiring for Scientist Python jobs?

Cities near Walnut, CA with the most Scientist Python job openings:

Scientist Python jobs near you

Data Scientist

YO AI Labs

Glendale, CA • On-site

Full-time

Re-posted 5 days ago

Job description

Job Description

  • Job title: Data Scientist
  • Experience: 5-15 Years
  • Location: Glendale, USA
  • Job Type: Full-time


Must Haves:

  • Python Machine Learning, data science, AWS, Statistical Modeling, Semantic Search, Vector DB, GenAI, SQL

Qualifications:

  • Bachelors in Statistics, Economics, Computer Science, Engineering, Mathematics, Physics, or a related field + 7 years of experience with an emphasis on experimentation or causal inference.
  • Strong background in statistical modelling: regression, classification, time series forecasting, causal inference, and other techniques.
  • Robust knowledge of causal inference approaches such as propensity scores, synthetic controls, difference-in-differences, doubly robust methods, meta learners, and uplift modeling.
  • Expertise in A/B test design, execution, statistical modeling, and sophisticated causal inference techniques.
  • Proficient in conducting sample size calculations, power analysis, and minimum detectable effect estimation.
  • Experience managing multiple testing scenarios and controlling false discovery rates.
  • Ability to deploy both Bayesian and frequentist statistical approaches.
  • Deep understanding of assumptions required for causal inferences, including the foundational statistical concepts that underpin the approaches.
  • Proven ability to manage end-to-end experimentation and causal inference analyses, from initial requirements to impactful outcomes
  • Advanced skills in Python and/or R-including development of statistical analysis packages, and use of ML frameworks (e.g., scikit-learn, LGBM).
  • Strong communication skills for translating complex data into actionable narratives and presenting confidently to technical and non-technical audiences, including senior executives.

Key Responsibilities:

  • Design and Execute Experiments: Lead end-to-end A/B testing initiatives and Geo Experiments, from hypothesis formation and experimental design to statistical analysis and business recommendations.
  • Advanced Statistical & Causal Inference: Apply deep knowledge of experimental design, regression, classification, causal inference and ensure proper assumptions.
  • Build Scalable Solutions: Develop experimentation and causal inference tools and frameworks that can scale across Disney's businesses.
  • Deliver Strategic Insights: Partner with stakeholders to identify optimization opportunities and translate complex analytical findings into clear business recommendations.
  • Influence Executive Decisions: Present findings and recommendations to senior leadership, effectively communicating statistical concepts to non-technical stakeholders.


Preferred Qualifications:

  • MS in computer science, statistics, math or a related quantitative field +5 years of relevant experience OR PhD + 3 years of relevant experience with an emphasis on experimentation or causal inference.
  • Experience with ETL and data engineering: data extraction, transformation, integration, and quality controls for analytics at scale.
  • Skilled in production deployment and monitoring of data science solutions, including CI/CD pipelines, automated reporting, and ongoing experiment/model monitoring.
  • Familiarity with data platforms and applications such as Databricks, Jupyter, Snowflake, and Github.
  • Strong strategic business insight, preferably in subscription-based business models, with ability to apply experimentation and analytics to market trends and consumer insights.
  • Proven track record of leadership and stakeholder/project management, including influencing cross-functional teams and delivering high-impact outcomes.
  • Adept at adapting quickly to shifting priorities in a fast-moving environment while maintaining quality.
  • Drive and maintain a culture of quality, innovation and experimentation.
  • Demonstrated experience mentoring colleagues on best practices and technical concepts for building large scale solutions.