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Weekend Data Science Jobs in Monrovia, CA (NOW HIRING)

YO AI Labs

Data Scientist

Glendale, CA

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 ...

Omnicom

Data Science and Analytics_08M

Los Angeles, CA · On-site

Set the vision, strategy and roadmap to deliver bleeding-edge marketing sciences solutions on your portfolio of clients. Defining and executing the data strategy: Uncover data needs/opportunities and ...

Omnicom

Data Science and Analytics_04

Los Angeles, CA · Hybrid

Data Science and Analytics The Marketing Science team is pivotal in the delivery of modern agency services. We are tightly integrated with planning and investment teams to deliver on and exceed our ...

Omnicom

Data Science and Analytics_04

Los Angeles, CA · On-site

Data Science and Analytics The Marketing Science team is pivotal in the delivery of modern agency services. We are tightly integrated with planning and investment teams to deliver on and exceed our ...

Omnicom

Data Science and Analytics_04

Los Angeles, CA · Hybrid

Data Science and Analytics The Marketing Science team is pivotal in the delivery of modern agency services. We are tightly integrated with planning and investment teams to deliver on and exceed our ...

Omnicom

Data Science and Analytics_04

Los Angeles, CA · On-site

Data Science and Analytics The Marketing Science team is pivotal in the delivery of modern agency services. We are tightly integrated with planning and investment teams to deliver on and exceed our ...

REVOLVE GROUP

Data Scientist

Cerritos, CA · On-site

$90 - $120/hr

Main purpose of the Data Science Analyst role: Use a diverse skill sets across math and computer science, dedicated to solving complex and analytically challenging problems here at Revolve. Major ...

New

EVgo Services LLC

Data Scientist

Los Angeles, CA · On-site

$100.70 - $125.90/hr

You will work closely with the Data Science R&D team to report issues and improve our analytic systems. Our team supports operations, hardware, and software groups at EVgo helping to identify ...

REVOLVE

Data Scientist

Cerritos, CA · On-site

$90K - $120K/yr

Main purpose of the Data Science Analyst role: Use a diverse skill sets across math and computer science, dedicated to solving complex and analytically challenging problems here at Revolve. Major ...

REVOLVE

Senior Data Scientist

Cerritos, CA · On-site

$120K - $150K/yr

Use a diverse skill sets across math and computer science, dedicated to solving complex and ... Mentor junior data scientists and analysts, providing guidance on best practices and methodologies

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All JobsData Science JobsWeekend Data Science JobsWeekend Data Science Jobs in Monrovia, CA

Weekend Data Science information

See Monrovia, CA salary details

$39.8K

$130.2K

$208.4K

How much do weekend data science jobs pay per year?

As of Sep 4, 2026, the average yearly pay for weekend data science in Monrovia, CA is $130,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,400.00 and $144,200.00 per year, depending on experience, location, and employer.

What is a weekend data science?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What skills and qualifications are needed to thrive as a weekend data scientist?

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What challenges do data scientists working on weekends face, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends depending on project deadlines, company policies, or client needs. Typically, data science roles involve regular weekday hours, but some positions require weekend work, especially in roles with flexible or project-based schedules. It is important to clarify work hours during the hiring process or in job descriptions.

What are the most commonly searched types of Data Science jobs in Monrovia, CA?

The most popular types of Data Science jobs in Monrovia, CA are:

What are popular job titles related to Weekend Data Science jobs in Monrovia, CA?

For Weekend Data Science jobs in Monrovia, CA, the most frequently searched job titles are:

What job categories do people searching Weekend Data Science jobs in Monrovia, CA look for?

The top searched job categories for Weekend Data Science jobs in Monrovia, CA are:

What cities near Monrovia, CA are hiring for Weekend Data Science jobs?

Cities near Monrovia, CA with the most Weekend Data Science job openings:

Weekend Data Science jobs near you

Data Scientist

YO AI Labs

Glendale, CA

Full-time

Re-posted 3 days ago

Job description

Must Have:

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 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 (difference-in-differences, propensity scores, instrumental variables), 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.

Basic 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 modeling: 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.
  • 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.