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Temporary Machine Learning Quant Jobs in Missouri

... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python and SQL. * 10+ years of experience with machine learning/statistical modeling (e.g., regression ...

Imagery Scientist (EO) - Senior

Saint Louis, MO · Remote

$89K - $121.50K/yr

... quantitative analysis to make recommendations that improve data curation and development in support of Machine Learning algorithm testing and evaluation. The ideal candidate is an expert imagery ...

Exceptional analytical and quantitative problem-solving skills. * Experience with large dataset ... Deployment of machine learning models to cloud platforms to serve internal customers at scale.

Exceptional analytical and quantitative problem-solving skills. * Experience with large dataset ... Deployment of machine learning models to cloud platforms to serve internal customers at scale.

$133K - $147K/yr

As a Sr. AI/ML Engineer I , you'll design, develop, and deploy machine learning solutions ... Evaluate model performance using quantitative and qualitative metrics (e.g., accuracy, robustness ...

Sr. Data Scientist

Saint Louis, MO · On-site +1

$120K - $150K/yr

Requires Master's in Data Science, Statistics, Applied Mathematics, or closely-related quantitative field & 4 yrs experience building predictive machine learning, statistical models, and optimization ...

New

Exceptional analytical and quantitative problem-solving skills. * Experience with large dataset ... Deployment of machine learning models to cloud platforms to serve internal customers at scale.

... 5+ years of quantitative analysis experience in data science capabilities including data mining, predictive modeling, machine learning, statistical modeling, large scale data acquisition ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

... 5+ years of quantitative analysis experience in data science capabilities including data mining, predictive modeling, machine learning, statistical modeling, large scale data acquisition ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

The ideal candidate brings deep expertise in advanced analytics and machine learning, strong ... quantitative reasoning and/or mathematical modeling skills. * 10+ years of experience with Python ...

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Temporary Machine Learning Quant information

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Quant, and why are they important?

To excel as a Temporary Machine Learning Quant, you need strong quantitative analysis skills, proficiency in machine learning algorithms, and an advanced degree in a quantitative field such as mathematics, statistics, computer science, or engineering. Hands-on experience with programming languages like Python or R, familiarity with data analysis libraries (e.g., NumPy, pandas), and exposure to financial systems or platforms are typically required. Exceptional problem-solving abilities, adaptability, and effective communication help you stand out in this fast-paced environment. These competencies are crucial for developing and deploying data-driven models that inform trading strategies and deliver measurable business impact.

What are the typical responsibilities and challenges faced by a Temporary Machine Learning Quant in a financial firm?

As a Temporary Machine Learning Quant, you will often be tasked with quickly analyzing large financial datasets to develop and validate predictive models for trading strategies or risk assessment. Adapting to new team environments and rapidly understanding proprietary data systems can be challenging, especially given the short-term nature of the role. You'll collaborate closely with traders, data engineers, and other quants to implement solutions, and are usually expected to deliver actionable insights within tight deadlines. The fast-paced setting provides exposure to cutting-edge technologies and can be a stepping stone to more permanent quant or data science positions.

What does a Temporary Machine Learning Quant do?

A Temporary Machine Learning Quant is a professional who applies machine learning techniques to financial data and quantitative models, typically on a short-term or project-based contract. Their work may involve researching, developing, and implementing algorithms to analyze market trends, forecast prices, or optimize trading strategies. These roles are often found in investment banks, hedge funds, or fintech companies, and require strong programming, statistical, and financial skills. The 'temporary' aspect indicates the position is not permanent and usually fills a specific project or resource gap.

What is the difference between Temporary Machine Learning Quant vs Quantitative Analyst?

AspectTemporary Machine Learning QuantQuantitative Analyst
CredentialsDegree in Computer Science, Data Science, or related fields; programming skills in Python, R, or C++Degree in Finance, Economics, or Mathematics; strong analytical skills
Work EnvironmentTech-driven, research-focused, often in financial firms or hedge fundsFinancial institutions, investment banks, asset management firms
Industry UsageCommon in quantitative trading, algorithm development, and data-driven finance rolesUsed for risk management, trading strategies, and financial modeling

The Temporary Machine Learning Quant and Quantitative Analyst roles share overlapping skills in data analysis and finance but differ mainly in focus. The Machine Learning Quant emphasizes programming, algorithm development, and machine learning techniques, often in tech-heavy environments. In contrast, the Quantitative Analyst leans more toward financial modeling, market analysis, and risk assessment. Both roles are vital in finance but cater to different technical and strategic needs.

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 Temporary Machine Learning Quant jobs in Missouri? For Temporary Machine Learning Quant jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Quant jobs in Missouri look for? The top searched job categories for Temporary Machine Learning Quant jobs in Missouri are:
What cities in Missouri are hiring for Temporary Machine Learning Quant jobs? Cities in Missouri with the most Temporary Machine Learning Quant job openings:

Exploitation Specialist/Imagery Scientist (SAR) - Senior with Security Clearance

GRVTY

Saint Louis, MO

$88.90K - $121.50K/yr

Other

Posted 9 days ago


Job description

What Impact You'll Have GRVTY is seeking a motivated and experienced imagery scientist (SAR) to provide geospatial and imagery expertise and quantitative analysis to make recommendations that improve data curation and development in support of Machine Learning algorithm testing and evaluation. The ideal candidate is an experienced SAR imagery scientist with a passion for advanced scientific problem solving, imagery exploitation, and operational intelligence support. This role will drive solutions informed by specific phenomenology limitations and advantages of the sensors and platforms in mind.

What You'll be Owning * Assist the SAR lead in conducting assessment of potential differences between new sensor characteristics and capabilities compared to currently utilized platforms * Assess potential differences in metadata, data format, and data structure characteristics in regard to changes to databases, schemas, APis, and other ETL related processes for the ingestion and movement of data when integrating into the existing data operations pipeline * Ascertain how to acquire new data, potential latency associated with acquisition, data formats, and security domains * Determine how to pre-process and standardize the data to match existing data standards or to be transformed into a usable state for labeling and model testing purposes. This may include converting between file format types or tiling full-size images into specified sizes or geospatial bounds. What You Must Have * Active TS/SCI Clearance with the ability to obtain a CI/Poly * 4+ years as a SAR expert with understanding of collection, phenomenology, image formation process, and exploitation products.

* Experience SAR imagery quality metrics and sensor metadata describing impacts of geometry on phenomenology * Exhibit experience exploiting SAR to determine the occurrence and location of objects of interest * Exhibit experience communicating with a variety of technical and non-technical audiences on availability and capabilities of SAR imagery products, methodologies, procedures, and algorithms to enhance analysis. * Exhibit an understanding of the principles of remote sensing and imagery processing and advanced exploitation methods What Would be Nice to Have * Experience applying CV and machine learning (ML) techniques to SAR imagery and data to address intelligence problems