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Temporary Machine Learning Quant Jobs in Ohio (NOW HIRING)

Machine Learning Engineer II

Columbus, OH

$94.20K - $128.90K/yr

D. or Master's degree in a quantitative discipline (such as computer science, statistics, or mathematics) with a minimum of four years' experience applying advanced machine learning techniques to ...

Machine Learning Engineer II

Columbus, OH · On-site

$94.20K - $128.90K/yr

D. or Master's degree in a quantitative discipline (such as computer science, statistics, or mathematics) with a minimum of four years' experience applying advanced machine learning techniques to ...

... quantitative field and 2+ years professional experience in a data science, machine learning, or related analytical role * Deep understanding of machine learning algorithms, statistical modeling ...

Required : • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. • At least 2+ years of industry ...

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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 Ohio? The most popular types of Machine Learning Quant jobs in Ohio are:
What job categories do people searching Temporary Machine Learning Quant jobs in Ohio look for? The top searched job categories for Temporary Machine Learning Quant jobs in Ohio are:
What cities in Ohio are hiring for Temporary Machine Learning Quant jobs? Cities in Ohio with the most Temporary Machine Learning Quant job openings:
Machine Learning Engineer

Machine Learning Engineer

Radiance Technologies

Beavercreek, OH • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Job description

Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection. Additionally, this position will improve upon current methods for the automated processing and exploitation of large data sets. This will include R&D on projects involving the exploitation of data from sensors including investigation of state-of-the-art machine learning classification methods to detect, track, and characterize targets of interest.
Radiance Technologies is an employee-owned company with benefits that are unmatched by most companies in the Dayton OH area. Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, interesting assignments, educational reimbursement, competitive salaries and a pleasant work environment combine to make Radiance Technologies a great place to work and succeed.
Required Experience:
  • A working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
  • Experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Decision Trees, Dimensional Reduction, Neural Networks & Deep Learning, Feature Engineering

Required Skills & Qualifications:
  • Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, Statistics, or a related field
  • Strong programming skills in at least one of the following languages Python, Matlab, C++
  • Experience with Machine Learning APIs, such as TensorFlow, PyTorch, or Keras
  • Active Secret Clearance with ability to obtain and maintain a TS/SCI

Desired Skills:
  • ML for either natural language processing, computer vision, reinforcement learning, generative modeling, or equivalent experience
  • PhD in data science, mathematics, statistics, computer science, a physical science or engineering is strongly desired
  • A mathematical background (Probability and Statistics)
  • An experienced grasp of version control using Git for nonlinear workflows
  • Thorough understanding of working in research, development and production environments
  • Background in image science, imagery exploitation, spatial analysis, and computer vision are a plus
  • R&D on remotely sensed data to include modeling and development of algorithms.
  • Ability to work independently or in a team environment
  • Strong technical writing and oral communication skills
  • Active Top Secret/SCI clearance

Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.