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Ai Quant Jobs in Michigan (NOW HIRING)

micro1 AI

Engineering AI Evaluator (PhD)

Detroit, MI · Remote

$80 - $90/hr

No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work ... Apply sophisticated calculus and quantitative methodologies to problem-solving tasks * Ensure ...

micro1 AI

AI Training Specialist - Chemistry

Warren, MI · Remote

$70 - $90/hr

Conduct qualitative and quantitative chemical analyses and experiments to support product ... AI systems. Preferred Qualifications * Advanced degree (PhD preferred) in Chemistry or closely ...

micro1 AI

AI Training Specialist - Chemistry

Warren, MI · Remote

$70 - $90/hr

Conduct qualitative and quantitative chemical analyses and experiments to support product ... AI systems. Preferred Qualifications * Advanced degree (PhD preferred) in Chemistry or closely ...

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Ai Quant information

What is an AI quant?

An AI Quant, or Artificial Intelligence Quantitative Analyst, is a professional who combines expertise in quantitative finance and machine learning to develop advanced trading strategies, risk models, or analytics tools. AI Quants use algorithms, statistical models, and large datasets to identify patterns, forecast market trends, and make data-driven investment decisions. They often work in hedge funds, investment banks, or proprietary trading firms, collaborating with software engineers and other quants to implement and optimize AI-driven financial models.

How does an AI quant typically collaborate with data scientists, traders, and software engineers within a financial institution?

AI Quants often work closely with data scientists to develop and refine machine learning models using financial data, ensuring models are statistically robust and actionable. They collaborate with traders to translate complex quantitative signals into trading strategies that are practical and aligned with market objectives. Additionally, AI Quants partner with software engineers to implement and optimize these models for real-time deployment, ensuring that the underlying code is scalable, efficient, and reliable. This cross-functional environment requires strong communication skills and adaptability, as priorities can shift with market movements and technological advancements.

What are the key skills and qualifications needed to thrive as an AI quant, and why are they important?

To thrive as an AI Quant, you need a strong background in quantitative analysis, mathematics, statistics, and machine learning, often supported by an advanced degree in a quantitative field. Proficiency in programming languages like Python or C++, experience with data analysis libraries (such as NumPy, pandas, and TensorFlow), and familiarity with financial modeling tools are typically required. Strong problem-solving skills, attention to detail, and effective communication set top performers apart in this role. These skills are crucial for developing robust AI-driven trading strategies and ensuring accurate, data-driven decision-making in the fast-paced financial sector.

What is the difference between Ai Quant vs Data Scientist?

AspectAi QuantData Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or AIDegrees in computer science, statistics, or related fields; certifications vary
Work EnvironmentFinancial firms, hedge funds, or trading firms focusing on quantitative analysisTech companies, research labs, or any industry leveraging data analysis
Employer & Industry UsagePrimarily finance and trading industriesBroad across tech, healthcare, retail, and more
Common Search & Comparison IntentUnderstanding specialized quantitative roles in financeExploring data analysis careers across industries

Ai Quants focus on developing algorithms and models for financial markets, often requiring advanced quantitative skills and finance-specific knowledge. Data Scientists have a broader scope, applying statistical and machine learning techniques across various industries. While both roles involve data analysis and programming, Ai Quants are specialized in finance, whereas Data Scientists work in diverse sectors.

What are popular job titles related to Ai Quant jobs in Michigan? For Ai Quant jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ai Quant jobs in Michigan look for? The top searched job categories for Ai Quant jobs in Michigan are:
What cities in Michigan are hiring for Ai Quant jobs? Cities in Michigan with the most Ai Quant job openings:
Ai Quant jobs near you

Engineering AI Evaluator (PhD)

micro1 AI

Detroit, MI • Remote

$80 - $90/hr

Part-time

Re-posted 19 days ago

Job description

Role Title: PhD Engineer (Electrical, Mechanical, Chemical)


Role Type: Contractor


Location: Remote


micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to contribute to a high-impact customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Deliver authoritative written responses to complex engineering prompts in your area of expertise
  2. Review and interpret scientific literature to provide contextually accurate and current insights
  3. Design and document realistic experimental scenarios based on advanced engineering principles
  4. Analyze data and interpret results to inform AI training datasets with precision
  5. Apply sophisticated calculus and quantitative methodologies to problem-solving tasks
  6. Ensure clarity, accuracy, and completeness of all submitted materials based on provided guidelines
  7. Collaborate with project coordinators to refine prompt response quality as needed


Preferred Qualifications

  1. PhD in Electrical, Mechanical, or Chemical Engineering
  2. Demonstrated expertise in calculus, data analysis, research methodology, and experimental design
  3. Exceptional written and verbal communication skills with the ability to convey complex concepts clearly
  4. Strong literature review capabilities and familiarity with synthesizing scientific knowledge
  5. Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not required)
  6. Proven ability to produce "golden response" level deliverables with accuracy and completeness
  7. Detail-oriented mindset and commitment to high-quality, impactful contributions

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