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Reliability Data Scientist Jobs Near Me

ComResource

Data Scientist

Columbus, OH

ComResource is looking for a Data Scientist. Responsibilities: * Develop and validate predictive ... reliability of deployed models. * Actively engage with cross-functional team members including ...

Citizens

Sr Data Scientist- Generative AI

Columbus, OH · On-site

As a Senior Data Scientist, Generative AI & Agentic Systems, you will help drive the bank's AI ... Develop model monitoring, evaluation, and observability frameworks to measure quality, reliability ...

Huntington

Digital - Principal SRE

Columbus, OH · On-site +1

$53.50 - $71.25/hr

The ideal candidate will work closely with Digital SRE engineers, data scientists, DevOps, and operations teams to deliver robust, efficient, and automated systems that support business goals.

Huntington

Digital - Principal SRE

Columbus, OH · On-site +1

$53.50 - $71.25/hr

The ideal candidate will work closely with Digital SRE engineers, data scientists, DevOps, and operations teams to deliver robust, efficient, and automated systems that support business goals.

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How much do reliability data scientist jobs pay per year?

As of Aug 28, 2026, the average yearly pay for reliability data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

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Reliability Data Scientist jobs near you
A map of the United States highlighting the number of Reliability Data Scientist job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Reliability Data Scientist job openings in each state, with California having the most at 2 and Hawaii the least at 0.

Data Scientist

ComResource

Columbus, OH

Full-time

Posted 21 days ago

Job description

ComResource is looking for a Data Scientist.

Responsibilities:

  • Develop and validate predictive and prescriptive models using advanced analytical techniques including machine learning, statistical modeling, optimization, and simulation.
  • Perform rigorous feature engineering, iterative model improvement, and implement A/B testing strategies.
  • Deploy models into production environments adhering to best practices in DevOps, including documentation, version control, and continuous integration.
  • Conduct regular monitoring and maintenance of models, addressing performance degradation and proactively updating based on new data or evolving business needs.
  • Collaborate with Data Engineers and MLOps professionals to ensure seamless integration and operational reliability of deployed models.
  • Actively engage with cross-functional team members including business analysts, data engineers, architects, product management, and subject matter experts to align analytics solutions to strategic goals.
  • Mentor junior team members, conduct code reviews, and contribute to team skill development.
  • Evaluate emerging technologies and analytical tools and recommend adoption when beneficial.

Essentials:

  • Bachelor's degree in Data Science, Computer Science, Statistics, Economics, Information Systems, or a related quantitative field.
  • 3–5 years of practical experience in advanced analytics, predictive modeling, and feature engineering.
  • Strong programming proficiency in Python and SQL, and familiarity with scripting languages such as Bash or PowerShell.
  • Experience deploying models using DevOps methodologies including CI/CD, containerization, and version control with Git.
  • Demonstrated experience with common data science methodologies including decision trees, neural networks, regression, time-series analysis, PCA, and ensemble modeling.
  • Effective communication skills with the ability to clearly present complex insights to technical and non-technical stakeholders.
  • Understanding of data governance, privacy, and ethical considerations in data handling.

Desired:

  • Master's degree or relevant professional certifications.
  • Familiarity with cloud services including Oracle Cloud Infrastructure (OCI) and experience in multi-cloud environments such as AWS, Azure, or GCP.
  • Experience with model-drift detection and automated monitoring solutions.

Req ID: RB41579983