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Data Analytics Jobs in Baton Rouge, LA (NOW HIRING)

UOB

First Vice President, Data Analytics

Central, LA · On-site

$120 - $160/hr

Analyze macro and micro data (structured/less structured) to answer business questions via strategic analysis, machine learning/NLP models.* Coordinate with various internal and external business ...

New

EBRPHA

Housing Data Analyst

Baton Rouge, LA

Job Summary The Housing Data Analyst is responsible for providing financial and data analysis in support of the organization's affordable housing portfolio, with a primary focus on Low-Income Housing ...

Partners Southeast

Housing Data Analyst

Baton Rouge, LA · On-site

$40K - $60K/yr

Job Summary The Housing Data Analyst is responsible for providing financial and data analysis in support of the organization's affordable housing portfolio, with a primary focus on Low-Income Housing ...

Partners Southeast

Housing Data Analyst

Baton Rouge, LA · On-site

Job Summary The Housing Data Analyst is responsible for providing financial and data analysis in support of the organization's affordable housing portfolio, with a primary focus on Low-Income Housing ...

Varsity Tutors

Data Analysis Tutor

Baton Rouge, LA · Remote

$18 - $40/hr

... analytics positions, and data-driven decision-making responsibilities. * Conceptual Teaching & Problem-Solving: Skilled at teaching data manipulation, visualization creation, and insight extraction ...

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$47

$82

How much do data analytics jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for data analytics in Baton Rouge, LA is $47.90, according to ZipRecruiter salary data. Most workers in this role earn between $38.51 and $54.28 per hour, depending on experience, location, and employer.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, creating reports, and developing data models using tools like SQL, Excel, and Python or R. Strong analytical skills and knowledge of data visualization are essential for these positions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data specialist, or reporting analyst, focusing on collecting, processing, and analyzing data to support decision-making. They often use tools like Excel, SQL, and data visualization software, and may work in industries like finance, healthcare, marketing, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is the work for a data analytics?

A data analyst's work involves collecting, processing, and analyzing data to identify trends, support decision-making, and improve business outcomes. They use tools like Excel, SQL, and data visualization software, and often require strong analytical skills and attention to detail.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

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

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.
What are the most commonly searched types of Data Analytics jobs in Baton Rouge, LA? The most popular types of Data Analytics jobs in Baton Rouge, LA are:
What are popular job titles related to Data Analytics jobs in Baton Rouge, LA? For Data Analytics jobs in Baton Rouge, LA, the most frequently searched job titles are:
What job categories do people searching Data Analytics jobs in Baton Rouge, LA look for? The top searched job categories for Data Analytics jobs in Baton Rouge, LA are:
What cities near Baton Rouge, LA are hiring for Data Analytics jobs? Cities near Baton Rouge, LA with the most Data Analytics job openings:
Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Baton Rouge, LA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $99,637 per year, or $47.9 per hour.

Data Analytics Coordinator

Louisiana Primary Care Association

Baton Rouge, LA • On-site

Full-time

Re-posted 9 days ago

Job description

Position Title: Data Analytics Coordinator
Fulltime Exempt
Supervisor: Analytics and Research Manager | Healthcare Technology and Optimization Manager | HCCN Project Manager
Position Summary: The Data Analytics Coordinator at the Louisiana Primary Care Association (LPCA) is responsible for supporting comprehensive data analytics initiatives and research activities across LPCA's network of Federally Qualified Health Centers (FQHCs). This role leverages analytical tools and methodologies to extract meaningful insights from healthcare data, supporting evidence-based decision-making and quality improvement efforts. The Data Analytics Coordinator collaborates with cross-functional teams to ensure completeness and accuracy of reports for process improvement, research initiatives, and grant compliance, while supporting LPCA's mission to promote accessible, affordable, quality healthcare services for underserved populations.
Responsibilities:
  • Collaborate with cross-functional teams to identify research objectives and key performance indicators (KPIs),
  • Develop reports and organize data visuals to communicate findings to stakeholders,
  • Assist in designing and executing research studies, including surveys, experiments, and observational studies,
  • Stay up-to-date with industry trends and best practices in analytics and research methodology,
  • Support the development and implementation of data-driven strategies to drive business growth and optimize performance,
  • Perform ad-hoc analysis and provide actionable recommendations to stakeholders,
  • Compile data and ensure validity from multiple assessments to develop profiles for each grant,
  • Create surveys and coordinate administration of surveys,
  • Query and translate data visually into tables, charts, graphs, and narrative presentations to produce user-friendly reports,
  • Support compliance efforts company grants to protect the confidentiality and accuracy of data,
  • Analyze, synthesize, and interpret reports for use in decision-making.

Requirements:
  •  Bachelor's degree. Minimum of 1-2 years of relevant experience in data analysis, research, project coordination, or administrative support, preferably in healthcare or government settings
  • Experience with data collection methodologies and report preparation
  • Understanding of one or more data analysis tools and programming languages such as Python, R, SQL, etc.
  • Proficiency with Microsoft Office Suite, particularly Excel for data manipulation and analysis
  • Experience with data aggregation and data visualization tools like Excel and Smartsheet
  • Familiarity with population health tools like i2i and Azara (preferred)
  • Knowledge of report writing and data presentation techniques
  • Detail-oriented with a strong commitment to accuracy and quality,
  • Ability to work independently and collaboratively in a fast-paced environment,
  • Communicate effectively, verbally, and in writing.