ZipRecruiter

Log In

1

Temporary Machine Learning Quant Jobs in Ohio (NOW HIRING)

84.51˚

Lead Data Scientist (P3764)

Cincinnati, OH · On-site

... quantitative field. • 6+ years of experience applying machine learning to real-world problems with strong experience in search and recommender systems. Strong understanding of approaches such as ...

84.51°

Lead Data Scientist (P3764)

Cincinnati, OH · On-site

Bachelor's, Master's, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field. * 6+ years of experience applying machine learning to real-world ...

Deloitte

Data Science Consultant

Cincinnati, OH

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 experience outside ...

Deloitte

Data Science Consultant

Columbus, OH

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 experience outside ...

Deloitte

Data Science Consultant

Cleveland, OH

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 experience outside ...

AMEND Consulting

Data Scientist

Cincinnati, OH

Machine learning and predictive analytics * Forecasting and quantitative analysis Tools & Platforms * Power BI and Power Apps * Git for version control * n8n and Power Automate * Azure Logic Apps ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... related quantitative field. * PhD preferred in Engineering, Operations Research, Statistics ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... related quantitative field. * PhD preferred in Engineering, Operations Research, Statistics ...

Penske

Staff Data Scientist

Beachwood, OH · On-site

... related quantitative field. * PhD preferred in Engineering, Operations Research, Statistics ... Advanced experience developing and deploying machine learning models using Python and modern ML ...

AMEND Consulting

Data Scientist

Cincinnati, OH · On-site

Machine learning and predictive analytics * Forecasting and quantitative analysis Tools & Platforms * Power BI and Power Apps * Git for version control * n8n and Power Automate * Azure Logic Apps ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... Science or related quantitative field. PhD preferred in Engineering, Operations Research ...

Relativity

Principal Applied Scientist

Columbus, OH · On-site +1

... machine learning, or a closely related field * Master's or Ph.D. in Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline, or equivalent professional experience

next page

Showing results 1-20

People also search for

All JobsMachine Learning Quant JobsTemporary Machine Learning Quant JobsTemporary Machine Learning Quant Jobs in Ohio

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 are popular job titles related to Temporary Machine Learning Quant jobs in Ohio? For Temporary Machine Learning Quant jobs in Ohio, the most frequently searched job titles 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:
Temporary Machine Learning Quant jobs near you
CCB Risk Modeling - AI ML Sr. Associate

CCB Risk Modeling - AI ML Sr. Associate

JPMorgan Chase & Co.

Columbus, OH • On-site

Full-time

Medical, Retirement

Posted 3 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 467 frontline employees who took The Breakroom Quiz

46th of 141 rated banks

Job description

Job Description
The CCB Risk Modeling team is seeking talented professionals with expertise in machine learning, explainable AI (XAI), and responsible AI practices, with a focus on credit decision and fraud modeling applications. Our work centers on explainability, fairness, and algorithmic bias - understanding how modern AI systems reason and make decisions across ML systems, next-generation LLMs, and agentic workflows. The ideal candidate will drive these initiatives across model development, tooling, and cross-functional collaboration, ensuring AI/ML solutions meet ethical standards and regulatory expectations.
Key Responsibilities
  • Model Development: Design and develop machine learning models to drive impactful decisions across credit decisions and fraud modeling, covering the entire customer lifecycle, including acquisition, account management, transaction authorization, and collections.
  • Advanced Machine Learning Techniques: Apply state-of-the-art machine learning methodologies - including deep learning architecture, transformer-based models, and LLMs - on big data platforms to tackle complex business challenges.
  • Explainability & Fairness: Develop and maintain tools and frameworks that enhance AI/ML model explainability and fairness, ensuring transparency and ethical use of models.
  • Strategic Collaboration: Work closely with senior management to develop and implement ambitious, innovative modeling solutions, ensuring their successful deployment into production environments.
  • Cross-Functional Partnership: Collaborate with diverse teams, including risk, technology, model governance, and research, throughout the entire modeling lifecycle-from development and review to deployment and operational use.

Basic Qualifications
  • Ph.D. or Master's degree from a reputable institution in a quantitative discipline such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
  • 2 years of experience with data analysis in Python.
  • Proven track record in designing, building, and deploying high-quality machine learning models in production environments, demonstrating a strong ability to translate theoretical concepts into practical applications.
  • In-depth knowledge of advanced machine learning algorithms, including logistic regression, XGBoost, Deep Neural Networks (CNN and RNN), clustering, and recommendation systems, with expertise in model design, hyperparameter tuning, and responsible deployment practices.
  • Demonstrated experience in model interpretability and explainability for complex models such as XGBoost and GBM; experience extending these methods to deep learning architectures (CNNs, RNNs, transformers) is a strong plus.
  • Familiarity with large language models (LLMs) and their applications, including experience in fine-tuning, prompt engineering, and responsible deployment with appropriate safeguards, monitoring, and auditability.
  • Proficiency in Python, TensorFlow, PyTorch, Spark, or Scala, coupled with experience in big data technologies such as Hadoop, AWS, and Hive, and familiarity with MLOps tooling that supports model monitoring, drift detection, and end-to-end auditability.

Preferred Qualifications
  • Strong expertise, interest, and track record of performing cutting-edge research on Explainable AI

(XAI) and LLM.
  • Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired.
  • Strong ownership and execution; proven experience in implementing models in production.

About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
We offer a broad array of credit cards to meet the needs of individuals and small businesses, including Chase-branded and co-branded cards in partnership with well-known companies and organizations. Merchant Services is a leading provider of payment, fraud and data security for companies, capable of authorizing transactions across global currencies.

What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply