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Assistant Machine Learning Quant Jobs in Missouri

Develop and deploy predictive models, machine learning solutions, and AI capabilities to drive ... Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, or ...

Develop and deploy predictive models, machine learning solutions, and AI capabilities to drive ... Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, or ...

In this role, you'll explore novel approaches to machine learning, bridging cutting-edge ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Principal Data Scientist

California, MO ยท On-site

$200 - $260/hr

... machine learning. * Exceptional written and verbal communication -- ability to make complex ... D. in Statistics, Mathematics, Computer Science, or related quantitative field. Preferred

Key Responsibilities: * Assist in the scoping, execution, and completion of projects that align ... Develop and deploy machine learning, predictive analytics, and prescriptive analytics, including ...

If you are passionate about solving complex language challenges and advancing machine learning ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Champion production-grade machine learning practices, promoting scalable code and robust deployment ... quantitative field * 5+ years (or 2+ years with a Master's degree) of progressively complex data ...

Imagery Scientist (EO) - Senior

Saint Louis, MO ยท On-site +1

$160K - $190K/yr

What You'll be Owning * Assist the EO lead in conducting assessment of potential differences ... Experience applying CV and machine learning (ML) techniques to EO imagery and data to address ...

Senior, Data Scientist

Anderson, MO ยท On-site

$90K - $180K/yr

Minimum Qualifications Master's degree in computer science, Machine Learning, Operations Research, Statistics, Optimization, Data Analytics, Mathematics, or a closely related quantitative field. At ...

Senior, Data Scientist

Cassville, MO ยท On-site

$90K - $180K/yr

Minimum Qualifications Master's degree in computer science, Machine Learning, Operations Research, Statistics, Optimization, Data Analytics, Mathematics, or a closely related quantitative field. At ...

Senior, Data Scientist

Noel, MO ยท On-site

$90K - $180K/yr

Minimum Qualifications Master's degree in computer science, Machine Learning, Operations Research, Statistics, Optimization, Data Analytics, Mathematics, or a closely related quantitative field. At ...

Showing results 41-60

Assistant Machine Learning Quant information

What is an assistant machine learning quant?

Assistant Machine Learning Quants are entry-level professionals in quantitative finance who support senior quants by applying machine learning techniques to analyze financial data, build predictive models, and develop trading strategies. Their responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They work closely with quantitative researchers and traders to improve algorithmic trading systems and risk management processes. This role typically requires strong programming skills, a solid understanding of machine learning concepts, and familiarity with financial markets.

How does an assistant machine learning quant typically collaborate with senior quants and data scientists on projects?

As an Assistant Machine Learning Quant, you will often work closely with senior quantitative researchers and data scientists by supporting model development, data preprocessing, and feature engineering tasks. You may contribute to brainstorming sessions, implement prototypes, and assist in backtesting trading strategies or risk models. This collaborative environment provides valuable mentorship opportunities and exposure to best practices in quantitative analysis and machine learning within the finance industry. Effective communication and a willingness to learn from senior team members are key to success in this role.

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

To thrive as an Assistant Machine Learning Quant, you need strong quantitative skills, a background in statistics or mathematics, and typically a degree in a STEM field. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial modeling tools are essential. Strong problem-solving abilities, attention to detail, and effective communication are standout soft skills in this role. These competencies enable accurate model development, efficient data analysis, and clear collaboration with team members in high-stakes financial environments.
What are the most commonly searched types of Machine Learning Quant jobs in Missouri? The most popular types of Machine Learning Quant jobs in Missouri are:
What are popular job titles related to Assistant Machine Learning Quant jobs in Missouri? For Assistant Machine Learning Quant jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Assistant Machine Learning Quant jobs in Missouri look for? The top searched job categories for Assistant Machine Learning Quant jobs in Missouri are:
What cities in Missouri are hiring for Assistant Machine Learning Quant jobs? Cities in Missouri with the most Assistant Machine Learning Quant job openings:
Infographic showing various Assistant Machine Learning Quant job openings in Missouri as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Lead Security Cloud and AI Engineer

QUANTUM TECHNOLOGIES LLC

Saint Louis, MO โ€ข On-site

Other

Posted 3 days ago

New


Job description

Job Title: Lead Security Cloud and AI Engineer

Location: St. Louis, MO, USA

Duration: 12 Months + Extension

Bill Rate: $80,000

Job Type: W-2 Contract

Client: To Be Discussed Later

Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Summary:
As a Lead Security Cloud and Artificial Intelligences Engineer, you will shape the future of cybersecurity by designing, implementing, and enhancing secure cloud architectures while leveraging artificial intelligence and machine learning to strengthen security across IT, OT, and cloud environments. You will partner with cross-functional teams to develop intelligent threat detection, automate security operations, and build scalable solutions that improve visibility, accelerate response, and protect critical business systems. This role is ideal for a forward-thinking security professional who is passionate about cloud technologies, AI innovation, and delivering proactive, resilient cybersecurity solutions in a fast-paced, evolving environment.
Principal Essential Duties & Responsibilities

  • Design and implement secure cloud architectures with a strong emphasis on identity, network security, and data protection.
  • Configure and manage security controls across cloud services, including Entra ID, Key Vault, Storage, Azure Kubernetes Service, and networking.
  • Lead threat modeling, attack surface analysis, and risk assessments for cloud systems.
  • Implement and optimize cloud detection and response using tools such as Microsoft Sentinel and Defender for Cloud.
  • Develop and enforce security standards, policies, and governance frameworks.
  • Perform incident response, forensic analysis, and remediation for cloud-based threats.
  • Continuously assess and improve cloud security posture using benchmarks such as CIS and NIST.
  • Design and deploy artificial intelligence and machine learning models for security use cases.
  • Detect anomalies in logs and network traffic.
  • Enrich threat intelligence through artificial intelligence capabilities.
  • Develop user and entity behavior analytics.
  • Build and integrate large language model-powered systems.
  • Develop security copilots and investigation assistants.
  • Develop automated alert triage and summarization tools.
  • Develop data pipelines for ingesting, processing, and analyzing large-scale security data.
  • Build and integrate large language model-based solutions, including copilots, security assistants, and automated playbooks, using tools such as Azure OpenAI.
  • Evaluate and mitigate artificial intelligence-specific security risks, including prompt injection, data leakage, and model abuse.
  • Ensure responsible artificial intelligence practices, including model explainability and secure handling of sensitive data.
  • Apply artificial intelligence to automate security operations, reduce manual effort, and improve response time.

Minimum Education and Experience

  • Bachelor's degree in Computer Science, Cybersecurity, or a related field, or equivalent experience.
  • 7+ years of experience in cloud security, cybersecurity engineering, or related roles.
  • Strong expertise in Azure security services and cloud architecture.
  • Solid understanding of threat detection, incident response, and security operations.
  • Proficiency in Python or a similar programming language.
  • Hands-on experience with machine learning or data-driven systems.
  • Familiarity with large language models and prompt engineering.
  • Experience with tools such as Azure Machine Learning, Azure OpenAI, or equivalent platforms.
  • Understanding of data pipelines, feature engineering, and model evaluation.
  • Knowledge of MLOps concepts, including model lifecycle, monitoring, and retraining.

Preferred Education and Experience

  • Experience with Azure Cloud Policy for compliance and governance.
  • Experience with SIEM/SOAR platforms and security analytics.
  • Knowledge of adversarial machine learning and artificial intelligence security threats.
  • Familiarity with secrets management and certificate automation.
  • Working knowledge of Zero Trust Architecture.
  • Experience with SOC 2, HIPAA, or GDPR compliance in a cloud-native environment.
  • Ability to work cross-functionally and educate developers and operations teams on secure practices.

    Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.