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Quantitative Data Engineer Jobs in Ohio (NOW HIRING)

Monitise

AI Engineer

Columbus, OH

Bachelor's degree or higher in Computer Science, Data Science, Statistics, Engineering, Cybersecurity, or a related quantitative field or equivalent combination of education, related experience and ...

Fiserv, Inc.

AI Engineer

Columbus, OH · On-site

Bachelor's degree or higher in Computer Science, Data Science, Statistics, Engineering, Cybersecurity, or a related quantitative field or equivalent combination of education, related experience and ...

Keybank

Lead Quantitative Analytics Associate

Brooklyn, OH · On-site

$71K - $125K/yr

Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines * A minimum of 2 years of ...

US Bank

Quantitative Modeler Manager - AML

Columbus, OH · On-site

$53 - $68.50/hr

... data compilation, programming skills and qualitative analysis skills - Thorough knowledge of the quantitative and qualitative risk factors, industry risks, competition risks, and risk management ...

OpTech

Platform Engineer-Adaptiv

Cincinnati, OH · On-site

$51/hr

You'll work closely with Risk, Quantitative Analytics, Data Engineering, Infrastructure, and Technology teams to support critical business functions and regulatory processes. The ideal candidate ...

Smart Data

15787 Data Scientist II

Cincinnati, OH · On-site +1

LLM fine-tuning, prompt engineering, RAG pipelines, or agentic workflow development * Familiarity ... related quantitative field Preferred: * Experience with MLOps practices including workflow ...

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Quantitative Data Engineer information

What is a quantitative data engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

How does a quantitative data engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.

What are the key skills and qualifications needed to thrive as a quantitative data engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is the difference between Quantitative Data Engineer vs Data Scientist?

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

What are popular job titles related to Quantitative Data Engineer jobs in Ohio?

For Quantitative Data Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Quantitative Data Engineer jobs in Ohio look for?

The top searched job categories for Quantitative Data Engineer jobs in Ohio are:

What cities in Ohio are hiring for Quantitative Data Engineer jobs?

Cities in Ohio with the most Quantitative Data Engineer job openings:

Quantitative Data Engineer jobs near you

Data Science & Analytics Specialist

Riverside, OH • On-site

Apogee Engineering, LLC
See more jobs at Apogee Engineering, LLCexternal

Other

Posted 24 days ago

Job description

Overview

Apogee Engineering has a exciting position for aData Science & Analytics Specialist that will provide data science and analytics support to help design, implement, and refine analytic workflows leveraging NASIC data within cloud and enterprise environments. Works under the guidance of senior engineers and analysts to enable IA/AI/ML-enabled mission workflows.

****Contingent Upon Contract Award****

Responsibilities
  • Assist in developing and refining analytic workflows that operate on large, complex NASIC datasets.
  • Support the preparation and transformation of data for IA/AI/ML and advanced analytics.
  • Help conduct quantitative analysis, exploratory data analysis, and basic modeling to support mission objectives.
  • Document analytic processes, data flows, and results in support of technical reports and briefings.
  • Collaborate with systems engineers, software engineers, and mission analysts to align analytics with operational use cases.
Qualifications

MinimumExperience:

Citizenship:Must be a US citizenClearance:Ability to obtain and maintain a TS/SCI security clearance.

Education / Years of Experience:Additional Experience:

  • Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or related field, with at least two (2) years’ related experience (may include applied research, internships, or professional work).
  • Experience using data analysis tools or languages (e.g., Python, R, SQL, or similar).
  • Ability to interpret quantitative results and communicate them clearly in written and verbal form.
  • Familiarity with basic data management and data quality concepts.

Preferred Qualifications:

  • Experience supporting IA/AI/ML model development, evaluation, or integration.
  • Familiarity with cloud-based data and analytics platforms.
  • Experience working with intelligence or operational datasets (simulated or real).

Additional InformationLocation: Wright Patterson AFB Dayton, OHOn-site/Hybrid/Remote:On-siteTravel: Occasional

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