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Part Time Ai Analyst Jobs (NOW HIRING)

Weekday AI

Risk & Actuarial AI Expert

$100 - $120/hr

... Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a highly analytical and forward-thinking Risk & Actuarial AI Expert to join our growing team. This role sits ...

Weekday AI

Strategic finance AI Expert

$100 - $120/hr

... Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a Strategic Finance AI Expert to bridge advanced analytics with high-impact financial decision-making. This ...

Weekday AI

Financial modeling AI Expert

$100 - $120/hr

... Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a Financial Modeling AI Expert to join our team and play a critical role in bridging advanced analytics with ...

Weekday AI

Tax AI Expert

$100 - $120/hr

... Type: Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a ... Analyze complex tax datasets using advanced analytics and machine learning models to identify risks ...

EōS Fitness

Associate AI Solutions Analyst

Phoenix, AZ · On-site

$60K - $70K/yr

We are seeking an Associate AI Solutions Analyst to join our enterprise AI Operations team. This is ... Based on eligibility of tenure and full-time vs. part-time employment. EōS Fitness is an Equal ...

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Part Time Ai Analyst information

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$29.5K

$71.5K

$123K

How much do part time ai analyst jobs pay per year?

As of Jun 1, 2026, the average yearly pay for part time ai analyst in the United States is $71,511.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,500.00 and $79,000.00 per year, depending on experience, location, and employer.

What is the difference between Part Time Ai Analyst vs Data Scientist?

AspectPart Time Ai AnalystData Scientist
Required CredentialsBachelor's degree in CS, Data Science, or related field; some certifications in AI or machine learningBachelor's or Master's in CS, Data Science, or related; advanced certifications often preferred
Work EnvironmentPart-time roles, often freelance or contract, in tech companies or consulting firmsFull-time roles in tech, finance, healthcare, or research organizations
Employer & Industry UsageStartups, tech firms, consulting agencies focusing on AI projectsLarge corporations, research labs, and industries leveraging data-driven insights

The main difference is that a Part Time Ai Analyst typically works on specific AI projects on a part-time basis, focusing on data analysis and AI model support, while a Data Scientist usually holds a full-time position with broader responsibilities including data modeling, advanced analytics, and predictive modeling. Both roles require similar educational backgrounds and certifications, but differ mainly in work hours and scope of responsibilities.

More about Part Time Ai Analyst jobs
What are the most commonly searched types of Ai Analyst jobs? The most popular types of Ai Analyst jobs are:
What job categories do people searching Part Time Ai Analyst jobs look for? The top searched job categories for Part Time Ai Analyst jobs are:
Part Time Ai Analyst jobs near you
Infographic showing various Part Time Ai Analyst job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 6% Full Time, 91% Part Time, 1% Temporary, and 1% Contract. Highlights an 60% Physical, 8% Hybrid, and 32% Remote job distribution, with an average salary of $71,511 per year, or $34.4 per hour.

Risk & Actuarial AI Expert

Weekday AI

Remote

$100 - $120/hr

Part-time

Posted 11 days ago

Job description

This role is for one of our clients
Compensation: $100-$120 per hour (20 hours per week commitment)
Job Type: Part-time / Contract
Location: US, UK, Canada, France, Portugal (remote)
We are seeking a highly analytical and forward-thinking Risk & Actuarial AI Expert to join our growing team. This role sits at the intersection of actuarial science, risk management, and advanced analytics, leveraging artificial intelligence to enhance decision-making across insurance and risk portfolios. The ideal candidate will bring a strong foundation in actuarial principles combined with hands-on experience in data science, enabling the transformation of complex risk data into actionable insights.
Requirements
Key Responsibilities:
You will play a central role in evaluating and optimizing portfolio performance through detailed loss ratio and combined ratio analysis. This includes monitoring trends, identifying deviations, and providing recommendations to improve underwriting profitability. A deep understanding of claims behavior, pricing adequacy, and expense structures will be critical to success in this area.
In addition, you will conduct comprehensive portfolio risk assessments, using statistical models and AI-driven techniques to evaluate exposure across various lines of business. This involves identifying risk concentrations, assessing diversification, and supporting strategic decisions related to risk selection and capital allocation. You will collaborate closely with underwriting, finance, and product teams to ensure alignment between risk appetite and business objectives.
A significant part of the role will focus on catastrophe modeling and exposure management. You will work with catastrophe models and geospatial data to assess potential losses from natural disasters and extreme events. Enhancing traditional modeling approaches using machine learning techniques to improve prediction accuracy and scenario analysis will be a key expectation. You will also contribute to stress testing, scenario planning, and regulatory reporting requirements.
AI & Analytics Integration:
The role requires leveraging modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets. You will design and implement models that enhance pricing, reserving, and risk selection processes. Experience with tools such as Python, R, and cloud-based analytics platforms will be valuable.
Qualifications & Skills:
  • Bachelor's or Master's degree in Actuarial Science, Mathematics, Statistics, Data Science, or a related field
  • Progress toward actuarial certification (e.g., IFoA, SOA, or equivalent) preferred
  • 2-8 years of experience in actuarial analysis, risk management, or insurance analytics
  • Strong expertise in loss ratio and combined ratio analysis
  • Proven experience in portfolio risk assessment and risk modeling
  • Hands-on experience with catastrophe modeling tools and exposure management frameworks
  • Proficiency in programming (Python/R) and data visualization tools
  • Familiarity with machine learning techniques and their application in insurance
  • Strong problem-solving skills and ability to communicate complex insights to non-technical stakeholders

What We're Looking For:
We value individuals who combine technical rigor with business intuition. You should be comfortable working in a dynamic environment, handling ambiguity, and driving innovation through data. A proactive mindset, attention to detail, and the ability to translate analytical findings into strategic recommendations will set you apart in this role.

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