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Python Analytics Jobs in Cincinnati, OH (NOW HIRING)

Pwc

GenAI Python Systems Engineer-Manager

Cincinnati, OH

$99K - $232K/yr

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager & Summary ... Python and SQL - Experience with Docker and containerized deployments - Skilled in AI techniques ...

Keybank

Quant Analytics Mgr.

Cincinnati, OH · On-site

The Quantitative Analytics Manager leverages advanced mathematical knowledge, analysis ... Advanced Python/R/SAS: * Databases * Efficient coding * Can build strong code controls and ...

ClifyX

Azure Data Engineer (Python & AI/ML)

Cincinnati, OH · On-site

$111K - $134K/yr

Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2) • Advanced proficiency in Python (data processing, scripting, automation) • Strong ...

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How much do python analytics jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for python analytics in Cincinnati, OH is $56.25, according to ZipRecruiter salary data. Most workers in this role earn between $46.35 and $63.89 per hour, depending on experience, location, and employer.

What is a Python Analytics professional?

A Python Analytics professional is someone who uses the Python programming language to collect, process, analyze, and interpret data in order to help organizations make data-driven decisions. They often work with large datasets, perform statistical analyses, create data visualizations, and build predictive models. These professionals may work in industries such as finance, healthcare, marketing, or technology, and typically use libraries like Pandas, NumPy, and Matplotlib. Their work helps businesses gain insights, optimize processes, and solve complex problems through data.

What are the key skills and qualifications needed to thrive as a Python Analytics professional?

To thrive as a Python Analytics professional, you need a strong background in statistics, data analysis, and proficiency in Python programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data analytics libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and experience with databases are typically required. Strong problem-solving, communication, and critical thinking skills help in interpreting data and conveying insights to stakeholders. These abilities are crucial for turning complex data into actionable business decisions and driving organizational success.

What are some typical challenges faced by professionals in Python Analytics roles, and how can I prepare for them?

Professionals in Python Analytics roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and communicating insights effectively to non-technical stakeholders. To prepare, it's beneficial to strengthen your skills in data cleaning, visualization libraries (like Matplotlib or Seaborn), and learn best practices for writing efficient, reproducible code. Collaborating closely with data engineers, business analysts, and decision-makers is also a key part of the job, so developing strong communication and teamwork abilities will help you succeed.

What is the difference between Python Analytics vs Data Analyst?

AspectPython AnalyticsData Analyst
Required SkillsPython programming, data manipulation, statistical analysisExcel, SQL, basic statistics
CertificationsPython certifications, data analysis coursesNone typically required, but certifications like CAP or Microsoft certifications are common
Work EnvironmentData science teams, analytics departments, tech companiesBusiness units, marketing, finance, consulting firms
ToolsPython libraries (Pandas, NumPy, scikit-learn)Excel, SQL, Tableau, Power BI

Python Analytics involves using Python programming to perform advanced data analysis, modeling, and automation, often requiring coding skills. Data Analysts focus on interpreting data using tools like Excel and SQL, providing reports and insights. While both roles analyze data, Python Analytics typically involves more technical and programming expertise, making it suitable for complex data projects and predictive modeling.

What does a Python analytics do?

A Python analytics professional uses Python programming to analyze data, develop models, and generate insights for decision-making. They often work with data analysis libraries like pandas and NumPy, and may create visualizations or automate data processes. Strong programming skills and understanding of statistical methods are essential for this role.

What is the salary of Python analytics?

The salary for a Python analytics role typically ranges from $70,000 to $120,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, machine learning, and proficiency in tools like Pandas and NumPy tend to earn higher salaries.

What are popular job titles related to Python Analytics jobs in Cincinnati, OH?

For Python Analytics jobs in Cincinnati, OH, the most frequently searched job titles are:

What job categories do people searching Python Analytics jobs in Cincinnati, OH look for?

The top searched job categories for Python Analytics jobs in Cincinnati, OH are:

Python Analytics jobs near you
Infographic showing various Python Analytics job openings in Cincinnati, OH as of August 2026, with employment types broken down into 1% Internship, 90% Full Time, 6% Part Time, and 3% Contract. Highlights an 81% Physical, 6% Hybrid, and 13% Remote job distribution, with an average salary of $116,991 per year, or $56.2 per hour.

Lead Analyst, Insights & Analytics - Collections

Jobtailor

Cincinnati, OH • On-site

$85 - $110/hr

Other

Posted 9 days ago

Job description


  • Leads in the analysis of data activities and engagement across the assigned organization

  • Responsible for developing reporting, analytics, metrics and key performance indicators

  • Provide in-depth analysis and recommendations for improving/enhancing line of business performance

  • Assist in leading the education and development of less experienced staff

  • Collaborates with cross-functional teams and provides valuable data-driven insights

  • Responsible for manipulating large data files and transforming the data into business information that helps fulfill strategic objectives

  • Provides feedback and coaching to other data analysts


Requirements

  • Bachelor's degree in Computer Science, Management Information Systems, Business Analytics, Statistics, Mathematics, Economics, Engineering, Finance, or related field, or equivalent experience

  • Typically, minimum 6 years in banking, financial services, or similar background

  • Typically, minimum 6 years data analytics experience

  • Advanced in data analytics tools, languages, and methodologies such as SAS, SQL, R, Python, Tableau, Excel, or Power BI

  • Can write complex SQL queries against a variety of data sources and perform advanced data discovery.

  • Comprehensive understanding of collections metrics, reporting standards, and reporting experience strongly preferred


Core Competencies

Demonstrates expertise in data analytics, reporting, and performance metrics, with a strong ability to manipulate large data sets and provide actionable insights. Proven experience in coaching and developing less experienced staff while collaborating with cross-functional teams to achieve strategic objectives.


Highest-signal resume keywords

  • Data Analytics Experience

  • Advanced SQL Proficiency

  • SAS, SQL, R, Python, Tableau, Excel, Power BI

  • Reporting Standards Knowledge

  • Banking or Financial Services Background


ATS Optimization Keywords
Hard Skills

  • Data Analysis

  • Reporting Development

  • Key Performance Indicators

  • Complex SQL Queries

  • Data Transformation


Soft Skills

  • Coaching

  • Collaboration

  • Communication


Industry Keywords

  • Banking

  • Financial Services

  • Data Analytics

  • Collections Metrics

  • Business Analytics


Tools & Technologies

  • SAS

  • SQL

  • R

  • Python

  • Tableau

  • Excel

  • Power BI

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