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Freelance Python Data Analysis Jobs in Louisiana

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 ...

TSS Data Analyst Senior

Bossier City, LA · Hybrid

$85K - $107K/yr

Develop operational dashboards, performance scorecards, trend analysis, and data-driven ... Familiarity with Python or similar programming language * Strong project management skills, ability ...

... analysis and integration to support AI-driven initiatives - Utilizing programming languages such as Python and Java to enhance AI model deployment - Overseeing the creation and maintenance of data ...

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 ...

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Freelance Python Data Analysis information

What is freelance Python data analysis?

Freelance Python data analysis involves using the Python programming language to analyze and interpret data for clients on a project or contract basis. Freelancers in this field typically work with datasets to extract insights, visualize results, and help businesses make data-driven decisions. They often use libraries such as pandas, NumPy, and matplotlib, and may work across industries like finance, marketing, healthcare, and technology. Freelancers enjoy flexibility in choosing their projects and clients, and often work remotely.

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

To thrive as a Freelance Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and data manipulation, often backed by a relevant degree or proven portfolio. Experience with tools such as Pandas, NumPy, Jupyter Notebooks, and data visualization libraries like Matplotlib or Seaborn is typically required. Excellent problem-solving abilities, communication skills, and the ability to manage projects independently distinguish top performers in this role. These skills enable analysts to deliver actionable insights, meet client expectations, and maintain a successful freelance business.

What are some common challenges freelance Python data analysts face when working with clients remotely?

Freelance Python data analysts often encounter challenges such as clarifying project requirements, managing client expectations about deliverables, and ensuring timely communication across different time zones. Working remotely can also mean troubleshooting data access or security issues, especially if clients have strict data privacy policies. Building trust through regular updates and transparent reporting is key to successful collaborations in this role.
What are the most commonly searched types of Python Data Analysis jobs in Louisiana? The most popular types of Python Data Analysis jobs in Louisiana are:
What job categories do people searching Freelance Python Data Analysis jobs in Louisiana look for? The top searched job categories for Freelance Python Data Analysis jobs in Louisiana are:
What cities in Louisiana are hiring for Freelance Python Data Analysis jobs? Cities in Louisiana with the most Freelance Python Data Analysis job openings:
Infographic showing various Freelance Python Data Analysis job openings in Louisiana as of June 2026, with employment types broken down into 37% Full Time, 57% Part Time, 2% Temporary, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Healthcare Data Analyst (On-Site in Lafayette, LA)

FMOLHS

Lafayette, LA

Other

Posted 18 days ago


Job description

This role will be located on-site in Lafayette, LA.

The Healthcare Data Analyst 2 plays a crucial role in analyzing and interpreting complex health data to help improve patient outcomes, operational efficiency, and overall healthcare delivery within our health system. The ideal candidate will have advanced analytical skills, a strong understanding of healthcare data, and the ability to work collaboratively with various stakeholders across the organization.

Education: Bachelor's degree in Health Informatics, Data Science, Statistics, Public Health, Business/Healthcare Administration or a related field.

Experience: Minimum of 3 years of experience in healthcare data analysis or a related field including internship.

Technical Skills: Proficiency in data analysis tools and software, such as SQL, SAS, R, Python, or Tableau. Strong understanding of electronic health records (EHR) systems, healthcare databases, and data standards (e.g., ICD-10, CPT codes).

Analytical Skills: Advanced analytical and problem-solving skills. Ability to interpret complex data sets and provide meaningful insights.

Communication Skills: Excellent verbal and written communication skills. Ability to present data findings clearly and concisely to non-technical stakeholders.

Attention to Detail: Strong attention to detail and commitment to data accuracy and quality.

Team Player: Ability to work effectively in a collaborative, team-oriented environment.

Data Analysis and Reporting: Perform advanced data analysis to support clinical and operational decision-making. Generate comprehensive reports and data visualizations to communicate findings effectively.

Data Management: Ensure the accuracy, integrity, and security of healthcare data. Manage data extraction, transformation, and loading (ETL) processes.

Performance Metrics: Develop and monitor key performance indicators (KPIs) to assess the effectiveness of clinical and operational processes. Provide actionable insights to improve performance.

Research and Evaluation: Conduct research and evaluation projects to assess the impact of healthcare interventions and programs. Collaborate with clinical and administrative teams to design and implement studies.

Compliance and Standards: Ensure compliance with relevant regulations, standards, and best practices in healthcare data management and analysis.

Collaboration: Work closely with IT, clinical, and administrative teams to identify data needs and provide analytical support. Participate in cross-functional projects and initiatives.