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Entry Level Python Data Science Jobs in Los Angeles, CA

East West Bank

Financial Crimes Data Scientist

Pasadena, CA · On-site

$100K - $200K/yr

Python, SQL, Spark, Databricks * Cloud Analytics Platforms (Azure/AWS) * Programming Skills ... Hands-on experience with data science tools * Problem-solving aptitude * Analytical mind and great ...

New

East West Bank

Financial Crimes Data Scientist

Pasadena, CA · On-site

$100K/yr

Python, SQL, Spark, Databricks * Cloud Analytics Platforms (Azure/AWS) Qualifications * Programming ... Hands-on experience with data science tools * Problem-solving aptitude * Analytical mind and great ...

New

Excelhire

Data Analyst

Los Angeles, CA

$32/hr

... Science, or related field * 1-3 years of experience in data analysis (preferred) * Strong knowledge of Excel, SQL, and data visualization tools (Tableau/Power BI) * Basic knowledge of Python or R ...

Rule14

Data Scientist Machine Learning

Santa Monica, CA · On-site

$75K - $100K/yr

... science team focusing on predictive modeling, natural language processing, computer vision ... Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn

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How much do entry level python data science jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for entry level python data science in Los Angeles, CA is $63.17, according to ZipRecruiter salary data. Most workers in this role earn between $52.07 and $71.73 per hour, depending on experience, location, and employer.

What are some common challenges faced by entry-level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an Entry Level Python Data Scientist, and why are they important?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What is the difference between Entry Level Python Data Science vs Entry Level Data Analyst?

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

What are popular job titles related to Entry Level Python Data Science jobs in Los Angeles, CA? For Entry Level Python Data Science jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Entry Level Python Data Science jobs in Los Angeles, CA look for? The top searched job categories for Entry Level Python Data Science jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Entry Level Python Data Science jobs? Cities near Los Angeles, CA with the most Entry Level Python Data Science job openings:
Entry Level Python Data Science jobs near you
Infographic showing various Entry Level Python Data Science job openings in Los Angeles, CA as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $131,384 per year, or $63.2 per hour.
Financial Crimes Data Scientist

Financial Crimes Data Scientist

East West Bank

Pasadena, CA • On-site

$100K - $200K/yr

Full-time

Posted 6 days ago

New

Job description

Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement.
Headquartered in California, East West Bank (Nasdaq: EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a commitment to absolute integrity. East West Bank gives people the confidence to reach further.


Financial Crimes Data Scientist specializing in the development, deployment, and optimization of in-house AML and fraud detection models. Leverages machine learning, network analytics, and large-scale financial data to identify emerging threats, enhance detection effectiveness, reduce false positives, and support regulatory compliance across financial crime risk programs.


A Financial Crimes Data Scientist develops, validates, and deploys advanced analytics and machine learning solutions to detect, prevent, and investigate financial crimes, including money laundering, fraud, sanctions violations, and terrorist financing.

Key Responsibilities
  • Design, build, validate, and deploy in-house detection models for AML, fraud, and other financial crime risks.
  • Develop risk-scoring, anomaly detection, predictive, and network analytics models using internal and external data sources.
  • Create and optimize transaction monitoring scenarios and machine learning-driven alert generation frameworks.
  • Implement model deployment pipelines and production monitoring to ensure effectiveness and regulatory compliance.
  • Conduct feature engineering, model tuning, and performance assessment to improve precision, recall, and operational efficiency.
  • Partner with Compliance, BSA/AML, Fraud, Investigations, and Technology teams to translate emerging risks into scalable detection strategies.
  • Reduce false positives while increasing the identification of high-risk activity and suspicious behavior.
  • Support model governance, validation, documentation, and regulatory examinations.
  • Perform other duties as assigned.
Core Expertise
  • Financial Crime Risk Management
  • AML/BSA Compliance
  • Fraud Analytics
  • Machine Learning & AI
  • Graph and Network Analytics
  • Entity Resolution
  • Transaction Monitoring
  • Model Development & Deployment
  • Python, SQL, Spark, Databricks
  • Cloud Analytics Platforms (Azure/AWS)

  • Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
  • Statistics – Good applied statistical skills, including knowledge of statistical tests, behavior clustering, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies. 
  • Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques. 
  • Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description. 
  • Experience with Data Visualization Tools like Tableau and Power BI that help to visually encode data
  • Network/Link Analytics
  • Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
  • Strong Software Engineering Background
  • Hands-on experience with data science tools
  • Problem-solving aptitude
  • Analytical mind and great business sense

Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.


The base pay range for this position is USD $100,000.00/Yr. - USD $200,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.

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