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Assistant Machine Learning Quant Jobs in Missouri

... machine learning, and related quantitative work. * 6+ years of experience designing and ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML ... Contribute to the deployment of MLOps processes and techniques * Assist in the development of ...

The Data Team, which covers the full data spectrum of Machine Learning, Analysis and Data ... Have a strong quantitative background (statistics, ML, sciences, etc.) * Are fluent in Python and ...

Proficient in open-source programming languages and machine learning techniques, with a strong foundation in quantitative analysis. Highest-signal resume keywords * PhD In Quantitative Field * Open ...

Experience using machine learning and statistical analysis for building data-driven product solutions or performing methodological research. Core Competencies Demonstrates expertise in quantitative ...

Requires an MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, Operations Research, Engineering, Data Science, Economics, or a related quantitative discipline * Minimum ...

Translate complex business problems into data-driven analytics and machine learning tasks, then ... Minimum 2-year of professional experience in a Data Scientist or similar quantitative role ...

... machine learning to analyze vast internal and external datasets. This role is crucial for ... Quantitative Finance, Business Analytics, or a closely related quantitative field. • Minimum 2 ...

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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 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.

Machine Learning Specialist

Remote

Contractor

This job post has expired 2 days ago. Applications are no longer accepted.


Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Specialist based in Netherlands.

This is a remote opportunity for an experienced Machine Learning Specialist to design and deliver data-driven products and AI solutions.
You will work across machine learning, data science, analytics, and predictive modeling to solve complex business challenges.
The role combines hands-on technical delivery with collaboration across data, engineering, analytics, and project teams.
You will transform large and complex datasets into actionable insights, models, reports, and intelligent applications.
There is also an opportunity to influence broader AI initiatives by providing technical guidance and helping shape analytical products.
The position places strong emphasis on responsible AI, including privacy, transparency, accountability, and ethical data practices.
It is well suited to a technically strong professional who enjoys turning advanced analytics into practical business outcomes.

Accountabilities
  • Design, develop, train, validate, and evaluate machine learning models for business and enterprise use cases.
  • Analyze large and complex datasets to identify meaningful patterns, generate insights, and support data-driven decision-making.
  • Prepare, clean, normalize, structure, and organize data for predictive and prescriptive modeling.
  • Develop analytical models, data products, dashboards, reports, and visualizations that communicate findings effectively.
  • Integrate machine learning models into applications, business processes, and operational workflows.
  • Gather, clarify, and document business and technical requirements for AI and analytics initiatives.
  • Collaborate closely with data engineers, analysts, developers, and project teams to deliver end-to-end data solutions.
  • Provide technical leadership, guidance, and expertise across data science and AI initiatives.
  • Support the development of full-stack analytics and AI applications when required.
  • Promote responsible AI practices by considering privacy, accountability, transparency, security, and ethical implications throughout the development lifecycle.
  • Identify, communicate, and appropriately escalate technical risks, dependencies, and issues within a multi-vendor environment.
  • Develop and share reusable analytical models, methodologies, and data products to improve organizational capabilities.
Requirements
  • 6+ years of professional experience using statistical and programming languages for data analysis, machine learning, and related quantitative work.
  • 6+ years of experience designing and implementing analytical and quantitative models.
  • 6+ years of experience preparing and transforming data for predictive and prescriptive modeling.
  • 6+ years of experience applying AI and machine learning techniques to real-world business or enterprise challenges.
  • Strong understanding of data analysis methodologies, statistical techniques, predictive modeling, and machine learning concepts.
  • Demonstrated ability to work with large, complex datasets and translate analytical results into practical recommendations.
  • Strong programming and analytical capabilities, with the ability to develop robust, maintainable data and ML solutions.
  • Experience collaborating effectively with multidisciplinary teams, including data engineers, analysts, developers, and project stakeholders.
  • Ability to understand business requirements and translate them into appropriate technical and analytical approaches.
  • Strong communication skills, with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.
  • A responsible and thoughtful approach to AI development, with awareness of privacy, transparency, accountability, and ethical AI principles.
  • Ability to work independently, manage priorities, provide technical guidance, and escalate risks effectively in a complex delivery environment.
Benefits
  • Fully remote working arrangement.
  • Opportunity to work on AI, machine learning, analytics, and data-driven enterprise initiatives.
  • Exposure to complex business problems and large-scale datasets.
  • Cross-functional collaboration with data, engineering, analytics, and project teams.
  • Opportunity to provide technical leadership and influence the development of analytical data products.
  • Environment focused on responsible, transparent, and ethical use of AI.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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