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Intern Ai Math Analyst Jobs in Texas (NOW HIRING)

Aivra Health LLC

AI/ML Engineer Intern

Austin, TX · On-site

AI/ML Engineer Intern Location: New York, NY, USA (Hybrid/On-site/Remote) Job Type: Internship ... Strong analytical and problem-solving skills. * Good communication and teamwork abilities.

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Intern Ai Math Analyst information

What is the difference between Intern Ai Math Analyst vs Intern Data Scientist?

AspectIntern Ai Math AnalystIntern Data Scientist
Required CredentialsMath, Computer Science, or related field; some programming knowledgeStatistics, Computer Science, or related field; programming skills often required
Work EnvironmentTech companies, AI startups, research labsTech firms, finance, healthcare, research institutions
Employer & Industry UsageAI development, machine learning projectsData analysis, predictive modeling, data-driven decision making

Intern Ai Math Analysts focus on applying mathematical models to AI projects, often involving machine learning algorithms. Intern Data Scientists analyze large datasets to extract insights and build predictive models. While both roles require strong math and programming skills, Intern Ai Math Analysts are more specialized in AI and algorithms, whereas Intern Data Scientists emphasize data analysis and statistical methods.

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Intern Ai Math Analyst jobs near you
Infographic showing various Intern Ai Math Analyst job openings in Texas as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 64% Physical, 3% Hybrid, and 33% Remote job distribution.

AI System Analyst (AI Monte Carlo)

Saransh Inc

Houston, TX • On-site

Contractor

Posted 4 days ago

Job description

Role: AI System Analyst (AI Monte Carlo)
Client address: Houston, TX (Hybrid)
Contract
 
Experience Required: 10-12 years
 
Mandatory skills:
  • AI Monte Carlo
  • Python
     
Key Responsibilities:
  • Solution Architecture: Design and implement advanced Monte Carlo simulation frameworks to solve complex probabilistic problems (e.g., risk assessment, optimization, or predictive forecasting).
  • Client Engagement: Lead discovery sessions with clients to extract and define technical requirements from high-level business goals.
  • Cross-Functional Collaboration: Serve as the primary technical liaison between functional business units and core engineering teams to ensure alignment on deliverables.
  • End-to-End Delivery: Own the full lifecycle of AI development—from algorithmic design and data modeling to deployment and performance tuning.
  • Mentorship & Leadership: Provide technical guidance to junior/mid-level developers while maintaining the self-sufficiency to handle critical individual contributor tasks in agile environments.
Technical Qualifications:
  • Core AI & Math: Expert knowledge of Monte Carlo methods (MCMC, Sequential Monte Carlo, Quasi-Monte Carlo) and their application in AI/ML environments.
  • Programming: Mastery of Python or C++ (high-performance computing experience is a major plus).
  • Infrastructure: Solid understanding of cloud-based AI deployment (AWS, Azure, or GCP) and containerization (Docker/Kubernetes).
  • Strategic Thinking: 10+ years of experience navigating the trade