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Python Data Analyst Jobs in Louisiana (NOW HIRING)

Ascentt

Manufacturing Data Analyst

Iowa, LA · On-site

$80 - $100/hr

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and ... Python, Power BI / Tableau, Snowflake, Azure / AWS, ETL, Data Pipelines Industry Experience ...

New

GDIT

TSS Data Analyst Senior

Bossier City, LA · Hybrid

$85K - $107K/yr

Experience with Python * Experience with leading/managing and mentoring a small team of Data Analysts in support of development initiatives * Strong Excel background; familiarity with other Microsoft ...

GDIT

TSS Data Analyst Senior

Bossier City, LA · Hybrid

$85K - $107K/yr

As a Data Analyst Senior, you will help ensure today is safe and tomorrow is smarter. Our work ... Familiarity with Python or similar programming language * Strong project management skills, ability ...

Huntington

Senior Data Analyst, Public Website Performance In this role, you will be the dedicated analytics ... Technical fluency with large datasets, SQL, Python or R, business intelligence tools, and digital ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Louisiana

Python Data Analyst information

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$29.1K

$70.7K

$116.3K

How much do python data analyst jobs pay per year?

As of Aug 20, 2026, the average yearly pay for python data analyst in Louisiana is $70,668.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,400.00 and $82,900.00 per year, depending on experience, location, and employer.

What does a Python data analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

What does a Python data analyst do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

How do Python data analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

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

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

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.
More about Python Data Analyst jobs

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For Python Data Analyst jobs in Louisiana, the most frequently searched job titles are:

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Cities in Louisiana with the most Python Data Analyst job openings:

Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Louisiana as of August 2026, with employment types broken down into 2% Internship, 91% Full Time, 5% Part Time, and 2% Contract. Highlights an 77% In-person, 5% Hybrid, and 18% Remote job distribution, with an average salary of $70,668 per year, or $34 per hour.

Manufacturing Data Analyst

Ascentt

Iowa, LA • On-site

$80 - $100/hr

Other

Posted 2 days ago

New

Job description

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.

Role Overview

Are you someone who thrives at the intersection of data and real-world operations? We’re looking for a Manufacturing Data Analyst / Senior Data Analyst to drive a large-scale data transformation initiative across manufacturing plants—working directly on the ground where impact truly happens.

What You’ll Do
  • Work on-site at manufacturing plants to understand operations firsthand
  • Map and analyze plant operations, shop floor, and production data
  • Conduct current-state assessments and build data glossaries
  • Partner closely with business stakeholders, plant teams, and leadership
  • Identify high-impact, quick-win opportunities (micro-transformations)
  • Act as a trusted data consultant, not just a developer
What We’re Looking For
  • 6+ years of experience in data-focused roles
  • Strong foundation in:
    • Data Warehousing, Data Modeling, Data Structures
    • Data Mapping, Data Analysis
    • Data Governance, Data Architecture, Data Glossary
  • Experience with manufacturing / plant / industrial data (highly preferred)
  • Strong consultative skills: stakeholder management, process mapping, requirements gathering, data strategy
  • Ability to translate complex data into simple business language
Tools & Technologies (Must Have)

SQL, Python, Power BI / Tableau, Snowflake, Azure / AWS, ETL, Data Pipelines

Industry Experience (Important)

Manufacturing, Automotive, Industrial, Supply Chain, Production, Heavy Industry

Nice-to-Have

Lean Manufacturing, Six Sigma, IIoT, Smart Factory, Industry 4.0

Location & Travel
  • Highly on-site role
  • Preferred: Kentucky, Indiana, North Carolina (Raleigh)
  • Open to candidates willing to travel frequently or relocate
Why This Role?

This isn’t a typical data role.

You’ll be:

  • Building trust with plant teams
  • Driving real transformation from the ground up
  • Acting as a bridge between data strategy and shop-floor execution
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