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Learning Analytics Remote Jobs in Santa Clara, CA

QuickLaunch Analytics

Data Platform Engineer

Santa Cruz, CA · Remote

$117K - $140K/yr

At QuickLaunch Analytics, we help organizations simplify the complex world of data. As a Data ... Remote (USA) or hybrid (Santa Cruz County, CA) Compensation: The estimated base salary range for ...

QuickLaunch Analytics

Data Platform Engineer

Santa Cruz, CA · On-site +1

$132K - $158K/yr

... analytics. WhatYou'llDo * Design and deploy modern data platforms in Azure Databricks, including ... Remote(USA)or hybrid (Santa Cruz County, CA) Compensation:The estimated base salary range for this ...

YO AI Labs

AI Data Science Expert - Remote

San Jose, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

YO AI Labs

AI Data Science Expert - Remote

Palo Alto, CA · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics.

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How much do learning analytics remote jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for learning analytics remote in Santa Clara, CA is $46.41, according to ZipRecruiter salary data. Most workers in this role earn between $33.89 and $50.82 per hour, depending on experience, location, and employer.

What is a learning analytics remote job?

A Learning Analytics Remote job involves analyzing educational data to improve learning outcomes, all while working from a remote location. Professionals in this role use data analysis tools and techniques to track student engagement, performance, and behavior across digital learning platforms. They help educators and institutions make data-driven decisions to enhance teaching strategies and personalize learning experiences. Remote positions in this field offer flexibility and often require strong analytical, communication, and technical skills.

What are the key skills and qualifications needed to thrive as a learning analytics professional working remotely?

To excel as a Learning Analytics professional in a remote setting, you need strong analytical skills, a background in education or data science, and experience with quantitative and qualitative research methods. Familiarity with learning management systems (LMS), data visualization tools (like Tableau or Power BI), and programming languages such as Python or R is typically required. Excellent communication, time management, and self-motivation are vital soft skills for collaborating with distributed teams and stakeholders. These skills and qualities are essential for interpreting educational data, providing actionable insights, and driving continuous improvement in remote learning environments.

What are some common challenges faced by professionals in a remote learning analytics role, and how can they be addressed?

Professionals in remote learning analytics often encounter challenges such as ensuring clear communication with stakeholders across different time zones and maintaining data privacy when working with sensitive student information. Additionally, accessing and integrating data from various learning platforms can require strong technical skills and problem-solving abilities. Staying proactive with regular virtual check-ins, utilizing secure data management practices, and leveraging collaborative tools can help address these challenges and foster effective teamwork in a remote environment.

What are the most commonly searched types of Learning Analytics jobs in Santa Clara, CA?

The most popular types of Learning Analytics jobs in Santa Clara, CA are:

What are popular job titles related to Learning Analytics Remote jobs in Santa Clara, CA?

For Learning Analytics Remote jobs in Santa Clara, CA, the most frequently searched job titles are:

What job categories do people searching Learning Analytics Remote jobs in Santa Clara, CA look for?

The top searched job categories for Learning Analytics Remote jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Learning Analytics Remote jobs?

Cities near Santa Clara, CA with the most Learning Analytics Remote job openings:

Learning Analytics Remote jobs near you
Infographic showing various Learning Analytics Remote job openings in Santa Clara, CA as of June 2026, with employment types broken down into 62% Full Time, 25% Part Time, and 13% Contract. Highlights an 100% Remote job distribution, with an average salary of $96,531 per year, or $46.4 per hour.

Senior Principal Machine Learning Engineer - Optimization

PubMatic

Redwood City, CA • On-site, Remote

$153K - $211K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 14 days ago

Job description

Role: Hybrid in Redwood City, CA. (Will consider Remote for the right candidate)
Must have: Experience building large-scale prediction or optimization systems
PubMatic is the leading AI-powered ad tech company delivering measurable advertising performance through an intelligent, unified platform that connects buyers, publishers, data partners, and commerce media across CTV, mobile app, and omnichannel environments.
About the Role:
We are looking for a Senior Principal Machine Learning Engineer to help build the next generation of performance optimization capabilities for PubMatic's Activate platform.
This role is focused on applying machine learning, prediction, ranking, calibration, experimentation, and optimization techniques to improve campaign outcomes across performance advertising goals such as CTR, VCR, CPC, CPA, and ROAS. The ideal candidate has strong ML fundamentals and experience building large-scale production models or optimization systems.
What You'll Do:
  • Build and improve machine learning models for campaign optimization, prediction, ranking, bidding, forecasting, and calibration.
  • Develop models and algorithms that improve advertiser outcomes while balancing spend delivery, cost efficiency, campaign goals, marketplace dynamics, and system constraints.
  • Work on large-scale ML systems using signals from auctions, impressions, clicks, video events, conversions, users, context, inventory, campaigns, and marketplace feedback.
  • Design and improve CTR, CVR, VCR, CPA, ROAS, app-install, user-value, and campaign-performance models.
  • Develop bidding, pacing-aware optimization, ranking, exploration, and value-estimation approaches for performance advertising.
  • Improve model calibration, online/offline evaluation, experimentation, observability, and production feedback loops.
  • Reason through sparse conversions, delayed feedback, biased logs, cold-start campaigns, attribution noise, and online/offline metric mismatch.
  • Partner with performance advertising signal engineers to define model-ready features, labels, attribution windows, negative examples, training datasets, and online serving requirements.
  • Partner with engineering, product, analytics, and platform teams to translate model outputs into real-time decisioning systems.
  • Help evolve Activate from a media buying execution platform into a performance optimization platform.
  • Provide technical leadership and mentorship to engineers and applied scientists working on performance optimization problems.
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Preferred Experience:
    • Experience in ads, search, recommendations, marketplaces, e-commerce, fintech, pricing, bidding, or real-time optimization systems.
    • Experience with performance advertising goals such as CTR, VCR, CPC, CPA, ROAS, app install, retargeting, or user-value optimization.
    • Familiarity with real-time bidding, programmatic advertising, ad serving, attribution, pacing, identity, incrementality, or performance advertising.
    • Experience with exploration/exploitation, counterfactual evaluation, uplift modeling, delayed-feedback modeling, or learning under biased logs.
    • Experience with model calibration, model observability, A/B testing, online experimentation, incrementality testing, or lift measurement.
    • Experience working cross-functionally with product, engineering, analytics, and business stakeholders.

We'd love for you to have:
  • 10+ years of experience building production machine learning, ranking, recommendation, prediction, optimization, ads, marketplace, bidding, or pricing systems.
  • Strong understanding of supervised learning, ranking, calibration, causal thinking, experimentation, statistical evaluation, and model monitoring.
  • Experience building large-scale prediction or optimization systems in production.
  • Experience with CTR/CVR prediction, conversion modeling, bid optimization, value modeling, forecasting, calibration, or performance optimization.
  • Strong ability to reason about model quality, business impact, system constraints, production tradeoffs, and online performance.
  • Experience working with large-scale data and distributed ML workflows.
  • Strong engineering skills in Python, Java, SQL, Spark, TensorFlow, PyTorch, XGBoost, or similar technologies.
  • Ability to provide technical leadership across ambiguous, high-impact optimization problems.
  • BS, MS, or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related technical field.

Additional Information
Return to Office: PubMatic employees throughout the globe have returned to our offices via a hybrid work schedule (3 days "in office" and 2 days "working remotely") that is intended to maximize collaboration, innovation, and productivity among teams and across functions.
Benefits: Our benefits package includes the best of what leading organizations provide such as, paid leave programs, paid holidays, healthcare, dental and vision insurance, disability and life insurance, commuter benefits, physical and financial wellness programs, unlimited DTO in the US (that we actually require you to use!), reimbursement for mobile and fully stocked pantries plus in-office catered lunches 5 days per week.
Diversity and Inclusion: PubMatic is proud to be an equal opportunity employer; we don't just value diversity, we promote and celebrate it. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
About PubMatic
PubMatic is one of the world's leading scaled digital advertising platforms, offering more transparent advertising solutions to publishers, media buyers, commerce companies and data owners, allowing them to harness the power and potential of the open internet to drive better business outcomes. Founded in 2006 with the vision that data-driven decisioning would be the future of digital advertising, we enable content creators to run a more profitable advertising business, which in turn allows them to invest back into the multi-screen and multi-format content that consumers demand.
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Compensation Disclosure
In accordance with applicable law, the below salary range provided is PubMatic's reasonable estimate of the total compensation for this role. New hires and current team members are typically compensated toward the middle of our pay range. The actual amount may vary, based on non-discriminatory factors such as location, experience, knowledge, skills and abilities. In addition to salary PubMatic also offers a bonus, restricted stock units, and a competitive benefits package.
Total Compensation Range
$260,000-$330,000 USD

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