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Python Analytics Jobs in Wisconsin (NOW HIRING)

Proficiency in SQL, Python, R, or similar languages for data manipulation and analysis. * Expertise in analytics platforms and tools (e.g., Power BI, AWS/GCP/Azure cloud services, Databricks)

Strong proficiently in data analysis tools (e.g., SQL, Python, R, Excel) and visualization techniques/software (e.g. Power BI, Tableau) * Proven experience in developing and implementing data ...

Business Analytics Tutor

Madison, WI ยท Remote

$18 - $40/hr

Adapts instruction using Excel, Tableau, Python, or R with real business data sets and case studies to support undergraduate and MBA students developing analytical capabilities for modern business ...

Business Analytics Tutor

Milwaukee, WI ยท Remote

$18 - $40/hr

Adapts instruction using Excel, Tableau, Python, or R with real business data sets and case studies to support undergraduate and MBA students developing analytical capabilities for modern business ...

Analytics Engineer - West Bend, Wisconsin Build What Helps Us Work Smarter. At Delta Defense, data ... Experience with with Python and shell scripting a plus * Experience with Agile development methods

Analytics Engineer - West Bend, Wisconsin Build What Helps Us Work Smarter. At Delta Defense, data ... Experience with with Python and shell scripting a plus * Experience with Agile development methods

... analytics team performing statistical analysis and/or data modeling * Proficient with SQL * Experience with Python or R * Experience working with data visualization tools (e.g., Tableau, PowerBI)

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Python Analytics information

What is the salary of a Python analyst?

The salary of a Python analyst typically ranges from $60,000 to $110,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, machine learning, and proficiency in tools like Pandas and Jupyter Notebook tend to earn higher salaries.

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

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.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.

Can I be a data analyst in 3 months?

Becoming a data analyst with a focus on Python typically requires several months of dedicated learning, including skills in data manipulation, visualization, and tools like pandas and SQL. While some individuals may acquire foundational skills in three months, gaining proficiency for a professional role usually takes longer and depends on prior experience and learning pace.

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.

Is Python still in demand?

Python analytics roles remain highly in demand due to Python's versatility in data analysis, machine learning, and automation. Employers seek professionals skilled in libraries like Pandas, NumPy, and frameworks such as TensorFlow, often requiring proficiency in data visualization and scripting. Staying updated with Python versions and related tools enhances job prospects in this field.

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 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 popular job titles related to Python Analytics jobs in Wisconsin? For Python Analytics jobs in Wisconsin, the most frequently searched job titles are:
Infographic showing various Python Analytics job openings in Wisconsin as of June 2026, with employment types broken down into 61% Full Time, 28% Part Time, and 11% Contract. Highlights an 72% In-person, 22% Hybrid, and 6% Remote job distribution.
Commercial Product Manager Lead for Risk Analytics and Data Quality

Commercial Product Manager Lead for Risk Analytics and Data Quality

Worldpay, Inc.

Milwaukee, WI โ€ข Hybrid

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Job Description

FIS is seeking a senior, hands-on leader to drive delivery across Risk Analytics and Data Quality initiatives. In this role, you will lead a hybrid team (domestic and offshore) and partner closely with stakeholders to plan, execute, and continuously improve analytics and data-quality solutions supporting risk and compliance priorities.

What you will do:

  • Lead day-to-day delivery for Risk Analytics and Data Quality workstreams, balancing people leadership with hands-on analytical execution.

  • Supervise, coach, and develop a team of domestic and offshore data professionals; coordinate workload, priorities, and delivery commitments.

  • Partner with stakeholder teams across Risk Analytics and Enterprise Data Management to scope work, set expectations, and deliver results.

  • Own project planning, execution, and reporting for assigned initiatives; manage resources and risks to meet timelines and quality expectations.

  • Establish and maintain standards for documentation, reproducibility, scalability, and model/data governance.

Risk Analytics responsibilities

  • Plan, develop, and deliver analytical models including classification and predictive models, scoring and rules-based models, and other advanced analytics techniques (machine learning and artificial intelligence).

  • Perform problem framing and analysis; lead data collection, integration, exploration, and preparation to support modeling objectives.

  • Guide model implementation in partnership with technology and business teams, ensuring solutions are production-ready and measurable.

  • Support analytics needs across Fraud Prevention, Anti-Money Laundering (AML), Compliance, Credit Risk, Market Risk, Operational Risk, and Finance.

  • Apply appropriate methodology across the model lifecycle, including tracking, documentation, reproducibility, scalability, monitoring, and actionable insights.

Data Quality responsibilities

  • Develop and oversee analytical controls and reporting to identify and track data-flow issues across systems and data sources.

  • Define and monitor critical data elements; detect unexpected values and potential quality defects.

  • Drive issue triage and resolution by partnering with stakeholders; track remediation through to closure.

Team & working style

  • You will lead a high-performing, globally distributed team supporting Risk Analytics and Data Quality initiatives. Success in this role requires strong collaboration across time zones and the ability to translate stakeholder needs into clear, executable plans.

Required Qualifications:

  • 10+ years of experience in banking and analytics, including senior-level stakeholder engagement and delivery ownership.

  • Graduate degree in Statistics, Data Science, Applied Economics, Machine Learning, or a related field (or equivalent experience).

  • Strong foundation in statistics, data science, and modern analytical techniques, including machine learning and AI concepts.

  • Proficiency with analytical programming and data tools such as Python, SAS, R, and SQL.

  • Experience leading teams and delivering work through clear planning, prioritization, and execution.

  • Excellent written and verbal communication skills, with the ability to explain complex analytical topics to technical and non-technical audiences.

  • Proficiency with Windows productivity tools (e.g., Microsoft Office).

Preferred Qualifications:

  • Working knowledge of Power BI.

  • Experience with Monday.com or a similar project management tool.


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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