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Volunteer Data Scientist Machine Learning Jobs in Ohio

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ... Lead Data Science Projects * Translate complex business requirements into robust, scalable ...

VTG

Data Scientist

Beavercreek, OH

The Data Scientist will design, prototype, and implement a data management and application ... machine learning based on the analysis of large sets of data * Experience with data storage and ...

Bread Financial

Lead Data Scientist

Columbus, OH · On-site

$144K - $250K/yr

Advanced machine learning modeling and/or technical expertise in developing market differentiation ... Bread Financial offers medical, prescription drug, dental, vision, and other voluntary benefits ...

Bread Financial

Lead Data Scientist

Columbus, OH · On-site +1

$144K - $250K/yr

Advanced machine learning modeling and/or technical expertise in developing market differentiation ... Bread Financial offers medical, prescription drug, dental, vision, and other voluntary benefits ...

Sidram Technologies

Data Scientist - w2

Columbus, OH · On-site

Data Scientist Contract to Hire Location - Columbus, OH Summary: Our banking client is seeking a ... Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ...

Flexjet

Machine Learning Engineer

Cleveland, OH · On-site

In this role, you will work alongside experienced engineers and data scientists to build, deploy, and maintain machine learning models. This is an excellent opportunity for someone early in their ...

Hudson Manpower

Data Scientist

Cincinnati, OH · On-site

$120 - $150/hr

Job Summary We are seeking an experienced Data Scientist to drive causal inference, experimentation ... Design and implement causal inference and causal machine learning solutions. * Measure the impact ...

Hudson Manpower

Data Scientist

Cincinnati, OH · On-site

$55 - $60/hr

Job Summary We are seeking an experienced Data Scientist to drive causal inference, experimentation ... Design and implement causal inference and causal machine learning solutions. * Measure the impact ...

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All JobsVolunteer Data Scientist Machine Learning JobsVolunteer Data Scientist Machine Learning Jobs in Ohio

Volunteer Data Scientist Machine Learning information

What does a volunteer data scientist machine learning do?

A Volunteer Data Scientist in Machine Learning applies data analysis and machine learning techniques to help organizations solve problems, often for nonprofits or community projects. They may work on tasks such as cleaning and analyzing datasets, building predictive models, or creating data visualizations. Their work supports impactful decision-making and can help organizations operate more efficiently or achieve specific social goals. Volunteers often collaborate with teams to define project objectives and deliver actionable insights using their technical expertise.

What skills and qualifications are needed to thrive as a volunteer data scientist machine learning?

To thrive as a Volunteer Data Scientist (Machine Learning), you need proficiency in statistics, data analysis, programming (Python or R), and a foundational understanding of machine learning algorithms, often supported by a relevant degree or online certifications. Familiarity with tools like scikit-learn, TensorFlow, Jupyter Notebooks, and data visualization platforms is typically required. Strong problem-solving abilities, teamwork, and effective communication are crucial soft skills for translating complex data insights to non-technical stakeholders. These skills and qualities are essential to effectively contribute value, support decision-making, and drive impact in resource-limited volunteer environments.

How does a volunteer data scientist machine learning typically collaborate with other team members or departments?

As a Volunteer Data Scientist specializing in Machine Learning, you will often work closely with cross-functional teams such as project managers, software engineers, and subject matter experts. Effective collaboration is essential, as you may need to clarify project goals, source and preprocess data, or translate complex findings for non-technical stakeholders. Regular meetings and open communication help ensure that your machine learning solutions are aligned with the organization's mission and that your insights are actionable. This collaborative environment provides valuable experience working in diverse teams and often leads to impactful, real-world applications of your technical skills.

What is the difference between Volunteer Data Scientist Machine Learning vs Volunteer Data Analyst?

AspectVolunteer Data Scientist Machine LearningVolunteer Data Analyst
Required CredentialsKnowledge of machine learning algorithms, programming skills (Python, R), basic statisticsProficiency in data visualization, basic statistics, Excel, SQL
Work EnvironmentCollaborative projects, research-focused, often remote or nonprofit settingsData reporting, dashboard creation, data cleaning in nonprofit or community projects
Employer & Industry UsageTech nonprofits, research institutions, startupsCharities, educational organizations, community initiatives

Volunteer Data Scientist Machine Learning focuses on developing predictive models and advanced analytics, requiring programming and machine learning expertise. Volunteer Data Analyst emphasizes data interpretation, visualization, and reporting. Both roles support nonprofits but differ in technical complexity and focus areas.

What are the most commonly searched types of Data Scientist Machine Learning jobs in Ohio?

The most popular types of Data Scientist Machine Learning jobs in Ohio are:

Volunteer Data Scientist Machine Learning jobs near you

Sr Data Scientist- Generative AI

Citizens Bank

Columbus, OH • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 18 days ago

Job description


Join a team where innovation meets impact. As a Senior Data Scientist, Generative AI & Agentic Systems, you will help drive the bank's AI transformation by designing, developing, and deploying Large Language Model (LLM) solutions, Retrieval-Augmented Generation (RAG) systems, AI agents, and intelligent automation capabilities. You will work across business, technology, risk, and compliance teams to deliver responsible, scalable, and production-ready GenAI solutions that improve customer experiences, enhance operational efficiency, and create measurable business value.
This role is ideal for an experienced data scientist with strong software engineering and machine learning skills, deep expertise in NLP and Generative AI, and experience developing AI solutions within highly regulated environments.
Key Responsibilities
  • Design, develop, and deploy production-grade Generative AI solutions using LLMs, RAG frameworks, AI agents, and workflow orchestration platforms.
  • Build intelligent document processing capabilities for information extraction, summarization, classification, question answering, and conversational AI applications.
  • Develop agentic workflows capable of autonomous reasoning, task execution, tool utilization, and multi-step decision support.
  • Design and implement retrieval pipelines, vector search architectures, embedding strategies, and knowledge-grounded AI systems.
  • Evaluate and improve LLM performance through prompt engineering, model benchmarking, hallucination reduction, and faithfulness testing.
  • Build scalable AI solutions using modern frameworks and infrastructure including vLLM, LangChain, LangGraph, MLflow, Databricks, Snowflake, and cloud-native platforms.
  • Perform exploratory data analysis, feature engineering, and statistical analysis to support machine learning and GenAI model development.
  • Develop model monitoring, evaluation, and observability frameworks to measure quality, reliability, fairness, and operational performance.
  • Collaborate closely with Model Risk Management (MRM), Compliance, Audit, Legal, and Information Security teams to ensure responsible AI deployment.
  • Create technical documentation, model development artifacts, validation packages, and executive-level presentations.
  • Partner with product managers, engineers, data architects, and business stakeholders to identify and prioritize GenAI opportunities.
  • Stay current with advances in Generative AI, agentic systems, multimodal AI, foundation models, and emerging industry best practices.

Qualifications
Required
  • Ph.D. or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, or a related quantitative field.
  • 7+ years of experience in data science, machine learning, predictive analytics, or artificial intelligence.
  • 4+ years of hands-on experience developing NLP and Generative AI solutions.
  • Strong proficiency in Python and modern software development practices.
  • Experience developing and deploying LLM-based applications using commercial or open-source models.
  • Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search.
  • Experience with prompt engineering, prompt evaluation, and LLM performance optimization.
  • Strong understanding of machine learning algorithms, deep learning, statistical modeling, and model explainability techniques.
  • Experience working with structured and unstructured data at enterprise scale.
  • Experience collaborating with cross-functional stakeholders and communicating technical concepts to non-technical audiences.
  • Strong knowledge of model governance, validation processes, and documentation standards.

Preferred
  • Experience designing and deploying AI agents and multi-agent systems.
  • Experience with agent orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, CrewAI, Autogen, or similar technologies.
  • Experience serving open-source LLMs using vLLM, Hugging Face, or equivalent inference frameworks.
  • Experience with RAG evaluation frameworks such as RAGAS or other LLM evaluation methodologies.
  • Experience with model monitoring, MLOps, and production AI deployment.
  • Experience with cloud AI platforms such as AWS Bedrock, Azure AI, Databricks, Snowflake Cortex.
  • Experience building document intelligence solutions involving PDFs, OCR, document extraction, knowledge extraction from images, and workflow automation.
  • Experience within banking, financial services, fintech, insurance, or other regulated industries.
  • Experience supporting Model Risk Management (MRM), model validation, audit reviews, or regulatory examinations.
  • Familiarity with MCP (Model Context Protocol), tool calling frameworks, and AI workflow automation platforms.

Technical Skills
Generative AI & LLMs
  • GPT, Claude, Llama and other foundation models
  • Retrieval-Augmented Generation (RAG)
  • AI Agents and Multi-Agent Systems
  • Prompt Engineering and Prompt Optimization
  • Fine-Tuning and Model Adaptation
  • LLM Evaluation and Guardrails
  • Knowledge Retrieval and Vector Search

Programming & Frameworks
  • Python
  • SQL
  • PyTorch
  • TensorFlow
  • Scikit-Learn
  • LangChain
  • LangGraph
  • Hugging Face

Data Platforms & MLOps
  • Experience with cloud-based data, AI, and ML platforms (AWS, SageMaker, Databricks, Snowflake, etc.)
  • Experience with distributed data processing frameworks (Spark / PySpark/Snowpark Snowflake)
  • Experience with ML lifecycle, orchestration, and deployment tools (MLflow, Airflow, CI/CD)
  • Experience with AI-assisted development and model monitoring solutions

NLP & Analytics
  • Text Classification
  • Information Extraction
  • Summarization
  • Topic Modeling
  • Question Answering
  • Sentiment Analysis
  • Explainable AI

Preferred Candidate Profile
The ideal candidate needs to demonstrate success building production-scale GenAI solutions such as RAG platforms, conversational AI systems, document intelligence solutions, AI agents, and automated decision-support systems. They possess strong technical depth, understand governance requirements in regulated industries, and can bridge the gap between cutting-edge AI capabilities and practical business outcomes. This individual is comfortable operating from concept through production deployment while maintaining a strong focus on quality, compliance, explainability, and measurable impact.
Hours & Work Schedule
  • Hours per Week: 40
  • Work Schedule: Monday - Friday
  • Hybrid: 4 days per week on-site, 1 day remote

Pay Transparency
The salary range for this position is $124,000- $165,000 per year, plus an opportunity to earn an annual discretionary bonus. Actual pay is based on various factors including but not limited to the budget, work location, and relevant skills and experience.
We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and more. Note, Citizens' paid time off policy exceeds the mandatory, paid sick or paid time-away policy of every local and state jurisdiction in the United States. For an overview of our benefits, visit https://jobs.citizensbank.com/benefits .
#LI-Citizens1
About Us
Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Equal Employment and Opportunity Employer
Job Applicant Data Privacy Policy
Background Check
Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.

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