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Python Data Scientist Jobs in Milwaukee, WI (NOW HIRING)

Rogers Behavioral Health

Data Analyst

Oconomowoc, WI · On-site

... Python, and others. Data Extraction and Utilization: * Collaborate with the team to develop a ... Bachelor's degree in a relevant field (e.g., computer science, math/statistics, economics ...

New

KOHLS

Senior Data Engineer (Remote)

Menomonee Falls, WI · On-site

$123K - $162K/yr

... Python, and Scala. * Build and manage cloud-based data ecosystems on GCP (BigQuery, Bigtable ... Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted ...

Deloitte

Project - Data Engineer

Milwaukee, WI · On-site

$112K - $135K/yr

Build and enhance data pipelines on AWS using Python to ingest, transform, and deliver data to ... Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or ...

Kohl's

Senior Data Engineer (Remote)

Menomonee Falls, WI · On-site

$123K - $162K/yr

... Python, and Scala. Build and manage cloud-based data ecosystems on GCP (BigQuery, Bigtable ... Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted ...

Marquette University

Data Engineer

Milwaukee, WI · On-site

$112K - $135K/yr

... Science, or a related field; or comparable experience. Minimum of 3 years' experience in data ... Python, R, PowerShell, or others). Strong Analytical and problem-solving skills Demonstrated ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102K - $141K/yr

... and implement scalable data architecture solutions for machine learning applications ... Linux Shell/CLI, Python, SQL, PowerShell, etc. • 2+ years of experience managing teams in ...

Generac

Senior Platform & Analytics Analyst

Waukesha, WI

$86K - $108K/yr

Bachelor's degree in Data Science, Computer Science, Industrial Engineering, Statistics, or a ... Proficiency in SQL, Python, R, or similar languages for data manipulation and analysis. * Expertise ...

KOHLS

MLOps Engineer II (Remote)

Menomonee Falls, WI · On-site

$97K - $134K/yr

What You'll Do * Collaborate with Data Scientists and Engineers across the full ML lifecycle ... Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit ...

New

Kohl's

MLOps Engineer II (Remote)

$99K - $136K/yr

Responsibilities : • Collaborate with Data Scientists and Engineers across the full ML lifecycle ... Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) • Experience ...

New

Continuus Technologies LLC

Senior Data Engineer

Germantown, WI · On-site

$107K - $146K/yr

... Science, Engineering, or related field (or equivalent experience) * 5+ years of experience in data engineering or related roles * Advanced SQL and strong proficiency in Python (or similar language)

KOHLS

Senior Data Engineer

Menomonee Falls, WI · On-site

$106K - $144K/yr

Proficiency in SQL and Python (or Scala) for data development, testing and automation Preferred * Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering or a related ...

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All JobsPython Data Scientist JobsPython Data Scientist Jobs in Milwaukee, WI

Python Data Scientist information

See Milwaukee, WI salary details

$36.9K

$120.8K

$193.4K

How much do python data scientist jobs pay per year?

As of Jul 2, 2026, the average yearly pay for python data scientist in Milwaukee, WI is $120,822.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $133,900.00 per year, depending on experience, location, and employer.

How much does a Python data scientist make?

A Python data scientist's salary typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals with advanced skills in machine learning, statistical analysis, and proficiency in tools like Pandas and TensorFlow tend to earn higher salaries.

Is Python useful in data science?

Python is a fundamental tool for data scientists, including those in the Python Data Scientist role, due to its extensive libraries such as pandas, NumPy, and scikit-learn that facilitate data analysis, visualization, and machine learning. Its simplicity and versatility make it a preferred programming language in the data science industry, often complemented by knowledge of SQL and data management skills.

What is the difference between Python Data Scientist vs Data Analyst?

AspectPython Data ScientistData Analyst
Required SkillsPython, machine learning, statistical analysis, data modelingExcel, SQL, basic statistics, data visualization
CertificationsData Science certifications, Python programming coursesData analysis or business intelligence certifications
Work EnvironmentData science teams, R&D, predictive modeling projectsBusiness units, reporting, data visualization tasks
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Python Data Scientists focus on building predictive models and advanced analytics using Python, while Data Analysts primarily interpret data through visualization and reporting. Both roles require strong analytical skills, but Python Data Scientists typically have more programming and machine learning expertise, making them suitable for complex data projects.

Is Python in high demand?

Python Data Scientists are in high demand across industries such as technology, finance, and healthcare due to Python's versatility and extensive libraries for data analysis, machine learning, and automation. Proficiency in Python, along with skills in data manipulation and visualization tools like Pandas and Matplotlib, can improve job prospects as organizations increasingly rely on data-driven decision making.

What are some common challenges faced by Python Data Scientists when working with large datasets?

Python Data Scientists often encounter challenges related to processing and analyzing large datasets, such as memory limitations and slow computation times. To address these, professionals typically use libraries like Pandas, Dask, or PySpark to optimize data handling and leverage parallel computing. Collaborating closely with data engineers and IT teams can also help in setting up efficient data pipelines and scalable infrastructure. Staying updated with best practices in data preprocessing and model optimization is crucial for managing these challenges effectively.

What is a Python Data Scientist?

A Python Data Scientist is a professional who uses Python programming language and its data analysis libraries to extract insights from large datasets. They apply statistical techniques, machine learning algorithms, and data visualization tools to solve business problems and make data-driven decisions. Python Data Scientists often work with tools like pandas, NumPy, scikit-learn, and Jupyter notebooks to manipulate data and build predictive models. Their role typically involves collecting, cleaning, analyzing, and interpreting complex data to help organizations make informed decisions.

Is 40 too late for data science?

Age is not a barrier to becoming a Python Data Scientist. Many professionals transition into data science later in their careers by acquiring relevant skills such as Python, machine learning, and data analysis, often through online courses or certifications. Success depends on your ability to learn, adapt, and build a strong portfolio of projects regardless of age.

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

To thrive as a Python Data Scientist, you need strong analytical skills, a solid understanding of statistics, machine learning, and proficiency in Python programming, typically backed by a degree in computer science or a related field. Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and version control systems like Git is essential. Problem-solving, curiosity, and effective communication are standout soft skills for this role. These abilities are crucial for extracting actionable insights from data, building predictive models, and collaborating across multidisciplinary teams.
What are popular job titles related to Python Data Scientist jobs in Milwaukee, WI? For Python Data Scientist jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Python Data Scientist jobs in Milwaukee, WI look for? The top searched job categories for Python Data Scientist jobs in Milwaukee, WI are:
Python Data Scientist jobs near you
Staff Data Engineer

Staff Data Engineer

Continuus Technologies LLC

Germantown, WI • On-site

Full-time

Posted 23 days ago

Job description

Role Overview

The Staff Data Engineer is a senior technical leader responsible for designing, scaling, and governing the organization's data platform and pipelines. This role sets data engineering standards, drives architectural decisions, and mentors engineers while partnering closely with analytics, product, and business leaders to enable reliable, high-impact data solutions.

Key Responsibilities

  • Architect and own scalable, resilient data pipelines and platforms

  • Lead design decisions for data ingestion, transformation, and storage

  • Establish best practices for data modeling, testing, observability, and reliability

  • Drive data quality, lineage, and governance frameworks

  • Serve as a technical mentor for junior and mid-level data engineers

  • Partner with analytics, product, and business stakeholders to translate needs into data solutions

  • Evaluate and implement modern data tools and cloud technologies

  • Lead incident response, root cause analysis, and long-term remediation

  • Contribute to roadmap planning and long-term data strategy

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)

  • 7+ years of experience in data engineering or related roles

  • Advanced SQL and strong proficiency in Python (or similar language)

  • Deep experience with data warehousing and data modeling

  • Proven experience designing production-grade ETL/ELT pipelines

  • Strong understanding of distributed systems and data architecture

Preferred Experience

  • Cloud data platforms (AWS, Azure, or GCP)

  • Orchestration and transformation tools (Airflow, dbt, Spark, Kafka, etc.)

  • Data observability, monitoring, and reliability tooling

  • Experience supporting analytics, BI, ML, or product data use cases

  • Prior experience influencing technical strategy without direct authority