ZipRecruiter

Log In

2

Python Pandas Remote Jobs in Redford, MI (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Strong proficiency in Python for data analysis and modeling (e.g., pandas, NumPy, Pyomo or similar ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

THOMSON REUTERS

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100.30K - $132.10K/yr

... remote teams. * Be an Agile Person:With a strong sense of urgency and a desire to work in a fast ... the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask ...

People also search for

All JobsPython Pandas JobsPython Pandas Remote JobsPython Pandas Remote Jobs in Redford, MI

Python Pandas Remote information

See Redford, MI salary details

$12

$54

$79

How much do python pandas remote jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for python pandas remote in Redford, MI is $54.08, according to ZipRecruiter salary data. Most workers in this role earn between $44.57 and $61.44 per hour, depending on experience, location, and employer.

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

To excel as a remote Python Pandas Data Analyst, you need strong proficiency in Python programming, advanced data manipulation skills with Pandas, and a solid understanding of statistics or data science principles, often backed by a relevant degree. Familiarity with tools like Jupyter Notebook, Git, SQL databases, and cloud data platforms is typically expected, along with certifications in data analysis or Python programming being advantageous. Excellent problem-solving, communication, and self-management skills help remote analysts collaborate effectively and deliver insights independently. These skills are vital for extracting and communicating actionable data insights while maintaining productivity and reliability in a remote work environment.

What are some common challenges faced by remote Python Pandas developers and how can they be addressed?

Remote Python Pandas developers often encounter challenges such as collaborating effectively with distributed teams, managing large datasets with limited local resources, and ensuring version control of data and code. To address these, it's helpful to establish clear communication channels (like Slack or Teams), utilize cloud-based data storage and computing platforms, and adopt collaborative tools like Git for code management. Regular virtual check-ins and thorough documentation also help maintain alignment and productivity in a remote setting.

What are Python Pandas Remote jobs?

Python Pandas Remote jobs are positions that require expertise in the Pandas library, a powerful data analysis tool in Python, and allow employees to work from any location outside of a traditional office environment. These jobs often involve data cleaning, manipulation, and analysis tasks, with responsibilities ranging from building data pipelines to generating insights from large datasets. Remote Pandas roles are common in industries like finance, healthcare, technology, and research, where data-driven decisions are essential. They typically require strong programming skills, problem-solving ability, and experience with distributed team collaboration tools.

What is the difference between Python Pandas Remote vs Data Analyst?

AspectPython Pandas RemoteData Analyst
Required SkillsPython, Pandas, SQL, data manipulationExcel, SQL, data visualization, basic programming
Work EnvironmentRemote, tech-focused companiesOffice or remote, various industries
CertificationsPython certifications, data analysis coursesData analysis, Excel, Tableau certifications
Industry UsageTech, finance, e-commerceFinance, marketing, healthcare

Python Pandas Remote roles focus on data manipulation using Python and Pandas, often in tech-driven environments. Data Analysts may use a broader set of tools like Excel and visualization software, working across various industries. While both roles involve data handling, Python Pandas Remote positions emphasize programming skills, whereas Data Analysts focus on interpreting data for business insights.

What cities near Redford, MI are hiring for Python Pandas Remote jobs? Cities near Redford, MI with the most Python Pandas Remote job openings:
Python Pandas Remote jobs near you
PLM Data Analyst - PV W2

PLM Data Analyst - PV W2

Tek Inspirations LLC

Dearborn, MI • Remote

Other

Posted 5 days ago

Job description

Job Description -

Title: PLM Data Analyst

Location: 4 days on site 1 Day remote In Dearborn, Michigan

LinkedIn, Visa and Dl copy

Sourcing Blueprint: What to Prioritize

1. The Ideal Candidate Profile

You are looking for a Data Quality Engineer or a PLM Migration Specialist from the manufacturing, automotive, or aerospace sectors. This is someone who enjoys cleaning up "dirty data" and building smart rules to automate repetitive data tasks.

2. Core Requirements to Screen For (Ranked by Importance)

  • PLM Fundamentals (Must Have): They must understand how product engineering data is structured. They need to know what a Bill of Materials (BOM) is, what an Item Revision is, and how CAD metadata connects.
  • The Python Scripting Stack: Since Java is handled by Ford's internal team, this candidate needs Python (specifically libraries like Pandas, NumPy, or Scikit-learn). They will use this to manipulate giant data sheets, find discrepancies, and build automated matching rules.
  • The "Manual to Automated" Mindset: They need to be someone who looks at a team doing manual Excel lookups or manual data entries and says, "I can write a script to automate 90% of this."

3. What to Avoid

  • ? Pure Java/C++ Application Developers (they will be bored and want to write code, not clean data).
  • ? High-level PLM Project Managers (they aren't hands-on enough to touch the staging databases).

4. Target Job Titles for LinkedIn

  • PLM Data Analyst
  • PLM Migration Specialist
  • PLM Data Quality Engineer
  • Manufacturing Data Engineer
  • PLM Functional Consultant

?? The Realistic Job Description

This streamlined version removes the confusing Java/C++ developer requirements and highlights the actual data automation, data profiling, and cleanup scope requested by the manager.

PLM Data Automation & Migration Engineer Ford IT

Role Overview

Ford IT is undergoing a massive enterprise modernization effort to migrate engineering data from legacy systems to a modern, unified platform. We are seeking a PLM Data Automation & Migration Engineer to join our team. The main challenge of this role is not writing core application code we have a dedicated team of software developers for that. Instead, this position is focused entirely on data correction, data quality, and migration automation.

Currently, our data validation and cleanup processes are manual. You will be responsible for leveraging Python and data-driven rule engines to build an automated framework that detects, profiles, and cleanses massive engineering data structures (BOMs, CAD metadata, and part revisions) before they are loaded into the target platform.

Key Responsibilities

  • Data Quality Automation: Move the team from manual data profiling to automation. Design and implement Python or rule-based scripts to scan, detect, and automatically resolve metadata discrepancies, attribute mismatches, and structure gaps.
  • Data Mapping & Transformation: Build and manage the intermediate data layers and staging databases (e.g., MongoDB, SQL) used to transform legacy data structures into clean unified models.
  • Cross-Functional Integration: Work closely with Ford s internal team of Java developers, translating data cleanup rules and mapping logic into functional requirements for the migration utility pipeline.
  • Engineering Data Stewardship: Maintain high data integrity for complex engineering structures, including Bills of Materials (BOMs), Item Revisions, and associated CAD datasets.

Required Skills & Qualifications

  • Experience: 4+ years of hands-on experience in PLM data engineering, data profiling, or data migration environments.
  • PLM Fundamentals: Strong foundational knowledge of Product Lifecycle Management (PLM) principles (e.g., Teamcenter, Windchill, Enovia, or similar) with a deep understanding of CAD structures, engineering changes, and BOM schemas.
  • Data Tooling: Proficient in Python and standard data analysis libraries (Pandas, NumPy, Scikit-learn) to write custom data cleansing and automated matching scripts.
  • Staging Databases: Hands-on experience querying and structuring data within staging layers or databases (such as MongoDB, PostgreSQL, or SQL Server).
  • Problem-Solving Background: Proven track record of handling complex data edge cases, resolving structure gaps, and migrating data from a legacy state to a modernized framework.
  • Prior experience with Teamcenter, 3DEXPERIENCE, or ENOVIA / XPDM data architectures.
  • Exposure to basic AI/ML automation or LLM-driven data parsing pipelines.

Apply