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Data Analyst Data Science Jobs in Ohio (NOW HIRING)

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets anddeveloping incloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

... Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess ... Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms ...

Preferred : • A degree in Computer Science, Statistics, Economics, Business or a related field is ... data analyst or similar role. • Solid understanding of machine learning concepts and hands-on ...

Analyze data for the purpose of identifying data anomalies, drawing conclusions and determining ... Other relevant work experience may be substituted Qualifications BS in Statistics, Computer Science ...

We are seeking an experienced Data Analyst to join our onshore team. This candidate should seamlessly utilize SQL, Python, Hadoop/Big Data and Tableau. Candidate should have functional knowledge in ...

Develop data analytics and visualizations by applying proven, industry-standard data science principles and techniques. Create and edit visual content, including charts, graphs, and dashboards, to ...

Preferred Skills Analytical Thinking, Competitive Advantages, Data Analytics, Data Management, Data Mining, Data Science, Machine Learning (ML), Microsoft Copilot, Microsoft Power Platform ...

Required : • 7+ years developing analytical solutions using advanced AI, Machine learning, and ... data science capabilities to supply chain and operations business problems • Ability to work in a ...

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Data Analyst Data Science information

See Ohio salary details

$13

$36

$62

How much do data analyst data science jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for data analyst data science in Ohio is $36.18, according to ZipRecruiter salary data. Most workers in this role earn between $26.11 and $43.85 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Data analysts and data scientists can start their careers at any age, including 40 or older. Success in data science depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, which can be learned at any stage of life. Many professionals transition into data roles later in their careers with dedication and continuous learning.

How do Data Analysts in Data Science typically collaborate with other departments or teams?

Data Analysts in Data Science frequently work cross-functionally, partnering with teams such as engineering, product management, marketing, and business intelligence. They translate complex data findings into actionable insights and tailor their communication to both technical and non-technical stakeholders. Regular collaboration may involve participating in meetings to understand business needs, designing dashboards for different teams, and providing data-driven recommendations to support company objectives. This collaborative environment not only enhances project outcomes but also fosters continuous learning and professional growth.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data analysts often use this concept to focus on the most impactful variables or features during analysis and modeling to improve efficiency and accuracy.

What does a Data Analyst in Data Science do?

A Data Analyst in Data Science collects, processes, and analyzes large sets of data to help organizations make informed decisions. They use statistical techniques and data visualization tools to identify trends, patterns, and insights from data. Their responsibilities often include cleaning data, creating reports, and communicating findings to stakeholders. Data Analysts play a key role in helping businesses optimize operations, understand customer behavior, and solve complex problems using data-driven approaches.

Can data science work as a data analyst?

Data science and data analysis are related fields, but they have different focuses. Data scientists often develop models and algorithms using programming languages like Python or R, while data analysts primarily interpret data, generate reports, and use tools like Excel or SQL. Skills in statistical analysis, data visualization, and understanding business needs are essential for both roles, and some professionals transition between them based on experience and training.

What is the difference between Data Analyst Data Science vs Data Engineer?

AspectData Analyst Data ScienceData Engineer
Required SkillsStatistics, programming (Python, R), data visualizationDatabase systems, ETL pipelines, programming (Python, Java)
Work EnvironmentAnalyzing data, building models, reportingBuilding and maintaining data infrastructure
CertificationsData Science certifications, SQL, PythonCloud certifications, database management
Industry UsageBusiness analysis, predictive modelingData infrastructure, big data systems

Data Analyst Data Science focuses on analyzing data and creating models to inform decisions, while Data Engineers build the systems that collect, store, and process data. Both roles require programming skills and often overlap in tools like Python and SQL, but their core responsibilities differ significantly.

What are the key skills and qualifications needed to thrive as a Data Analyst in Data Science, and why are they important?

To thrive as a Data Analyst in Data Science, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Familiarity with tools like SQL, Python or R, and data visualization platforms such as Tableau or Power BI, along with industry-recognized certifications, is highly valued. Attention to detail, problem-solving abilities, and effective communication skills help you interpret data insights and convey findings to stakeholders. These skills are crucial for transforming raw data into actionable intelligence that drives strategic business decisions.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and communicating findings effectively. Data analysts who develop skills in machine learning, programming, and data visualization will continue to be valuable in the evolving data science environment.
What job categories do people searching Data Analyst Data Science jobs in Ohio look for? The top searched job categories for Data Analyst Data Science jobs in Ohio are:
What cities in Ohio are hiring for Data Analyst Data Science jobs? Cities in Ohio with the most Data Analyst Data Science job openings:
Infographic showing various Data Analyst Data Science job openings in Ohio as of June 2026, with employment types broken down into 1% As Needed, 72% Full Time, 21% Part Time, and 6% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $75,263 per year, or $36.2 per hour.
Data Scientist

$85K - $122K/yr

Full-time

Posted 26 days ago


Procter & Gamble rating

8.4

Company rating: 8.4 out of 10

Based on 156 frontline employees who took The Breakroom Quiz

33rd of 518 rated manufacturers


Job description

Job Location

CINCINNATI GENERAL OFFICES

Job Description

Do you enjoy solving billion-dollar data science problems across trillions of data points? Are you passionate about working at the cutting edge of interdisciplinary boundaries, where computer science meets hard science? If you like turning untidy data into nonobvious insights and surprising business leaders with the transformative power of Artificial Intelligence (AI), including Generative and Agentic AI, we want you on our team at P&G.

As a Data Scientist in our organization, you will play a crucial role in disrupting current business practices by designing and implementing innovative models that enhance our processes. You will be expected to constructively research, design, and customize algorithms tailored to various problems and data types. Utilizing your expertise in Operations Research (including optimization and simulation) and machine learning models (such as tree models, deep learning, and reinforcement learning), you will directly contribute to the development of scalable Data Science algorithms. Your work will also integrate advanced techniques from Generative and Agentic AI to create more dynamic and responsive models, enhancing our analytical capabilities. You will collaborate with Data and AI Engineering teams to productionize these solutions, applying exploratory data analysis, feature engineering, and model building within cloud environments on massive datasets to deliver accurate and impactful insights. Additionally, you will mentor others as a technical coach and become a recognized expert in one or more Data Science techniques, quantifying the improvements in business outcomes resulting from your work.

Key Responsibilities:
  • Algorithm Design & Development: Directly contribute to the design and development of scalable Data Science algorithms.
  • Collaboration: Work closely with Data and Software Engineering teams to effectively productionize algorithms.
  • Data Analysis: Apply thorough technical knowledge to large datasets, conducting exploratory data analysis, feature engineering, and model building.
  • Coaching & Mentorship: Develop others as a technical coach, sharing your expertise and insights.
  • Expertise Development: Become a known expert in one or multiple Data Science techniques and methodologies.

Job Qualifications

Required Qualifications:

  • Education: Pursuing or has graduated with a Master’s degree in a quantitative field (Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, Physics, Analytics, etc.) or possess equivalent work experience.
  • Technical Skills: Proficient in programming languages such as Python and familiar with data science/machine learning libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas. Demonstrated ability to develop and test code within cloud environments.
  • Communication: Strong written and verbal communication skills, with the ability to influence others to take action.

Preferred Qualifications:

  • Analytic Methodologies: Experience applying analytic methodologies such as Machine Learning, Optimization, Simulation, and Generative and Agentic AI to real-world problems.
  • Continuous Learning: A commitment to lifelong learning, keeping up to date with the latest technology trends, and a willingness to teach others while learning new techniques.
  • Data Handling & Cloud: Experience with large datasets and developing in cloud computing platforms such as GCP or Azure.
  • DevOps Familiarity: Familiarity with DevOps environments, including tools like Git and CI/CD practices.

Immigration Sponsorship is not available for this role. For more information regarding who is eligible for hire at P&G along with other work authorization FAQ’s, please click HERE. 

Procter & Gamble participates in e-verify as required by law. 

Qualified individuals will not be disadvantaged based on being unemployed. 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Job Schedule

Full time

Job Number

R000135859

Job Segmentation

Entry Level

Starting Pay / Salary Range

$85,000.00 - $122,200.00 / year

What Procter & Gamble employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Procter & Gamble logo

About Procter & Gamble

Sourced by ZipRecruiter

Procter & Gamble (P&G), based in Cincinnati, OH, US, is a multinational consumer goods corporation. The company operates in the Consumer Discretionary sector and has a presence in various industries including Beauty, Health Care, Grooming, Fabric & Home Care, and Baby, Feminine & Family Care. Since its foundation by William Procter and James Gamble in 1837, P&G has grown to become a leading player in the consumer goods market. The corporation prides itself on its core values of leadership, ownership, integrity, passion for winning, and trust. They aim to improve consumers' lives in small but significant ways, with a mission to provide branded goods and services of superior quality and value.

Industry

Health and personal care stores

Company size

10,000+ Employees

Headquarters location

Cincinnati, OH, US

Year founded

1837