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Data Analytics Jobs in Alabama (NOW HIRING)

Mindlance is a company seeking a Data Analytics Analyst 1 to join their team. The role involves using tools like Python, R, and SQL for data analysis, as well as performing data integration and ...

Mindlance is seeking a high-energy Data Analytics Analyst who thrives on problem-solving and communicates with impact. The role involves building Power BI dashboards, analyzing business data for ...

Posting Details Position Information Posting Number F0997P Position Title Lecturer - Data Analytics Position Type Faculty Department Decision Systems and Sciences - Troy Division Sorrell College of ...

Data, Analytics & AI Engineer

Birmingham, AL · On-site

$107K - $128K/yr

Data, Analytics & AI Engineer Help Build the Future of Data, Analytics & AI Are you passionate about data engineering, analytics, and artificial intelligence? Do you love solving complex business ...

Data, Analytics & AI Engineer

Birmingham, AL · On-site

$107K - $128K/yr

Deploy. is seeking a Data, Analytics & AI Engineer to help design, build, and evolve a modern enterprise data platform. The role involves creating intelligent solutions that drive smarter decisions ...

... analytics · Ensure data integrity, consistency, and compliance with healthcare regulations (e.g., HIPAA) Reporting & Analytics · Design and maintain dashboards and reports for: o Provider ...

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Data Analytics information

See Alabama salary details

$22

$49

$85

How much do data analytics jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for data analytics in Alabama is $49.62, according to ZipRecruiter salary data. Most workers in this role earn between $39.86 and $56.20 per hour, depending on experience, location, and employer.

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 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 Alabama? The most popular types of Data Analytics jobs in Alabama are:
What cities in Alabama are hiring for Data Analytics jobs? Cities in Alabama with the most Data Analytics job openings:
Infographic showing various Data Analytics job openings in Alabama as of July 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $103,213 per year, or $49.6 per hour.

Data Analytics Analyst I

4pconsultinginc

Birmingham, AL • On-site

Contractor

Re-posted 5 days ago


Job description

Position: Data Analytics Analyst I

Location: Birmingham, AL
Contract : 3 Years
Client: Alabama Power
 

Position Overview

We are seeking a motivated Data Analytics Analyst I with 1–3 years of experience to support data analysis, reporting, data integration, and business intelligence initiatives.

The ideal candidate will have hands-on experience using tools such as Python, R, SQL, Tableau, Matplotlib, and Seaborn to analyze data, create visual reports, and deliver meaningful business insights. This role is well-suited for someone with strong analytical skills, attention to detail, and a desire to grow in data analytics, reporting, ETL, and predictive modeling.

Key Responsibilities

  • Collect, clean, analyze, and interpret data from multiple sources.
  • Use Python, R, SQL, and visualization tools to identify trends, patterns, and insights.
  • Build reports, dashboards, charts, and visual presentations for business users.
  • Support data extraction, transformation, and loading processes.
  • Work with databases and structured datasets to prepare data for analysis.
  • Perform statistical analysis and hypothesis testing to support business decisions.
  • Assist with predictive modeling and basic machine learning techniques.
  • Validate data accuracy and ensure reporting consistency.
  • Collaborate with business, technical, and operational teams to understand data needs.
  • Document data processes, reporting logic, and analysis results.

Required Qualifications

  • 1–3 years of experience in data analytics, reporting, business intelligence, or a related role.
  • Bachelor’s degree in Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, or a related field.
  • Proficiency with SQL for querying and analyzing data.
  • Experience with Python or R for data analysis.
  • Familiarity with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
  • Basic understanding of ETL processes and database concepts.
  • Strong analytical, problem-solving, and critical-thinking skills.
  • Strong attention to detail and ability to work with large datasets.
  • Good written and verbal communication skills.

Preferred Qualifications

  • Experience with machine learning or predictive analytics.
  • Familiarity with statistical analysis and hypothesis testing.
  • Experience working with multiple data sources and databases.
  • Knowledge of data cleaning, data validation, and data quality practices.
  • Exposure to business intelligence or dashboard development.

Key Skills

  • Data analysis and reporting
  • SQL querying
  • Python or R
  • Tableau / Power BI
  • Matplotlib / Seaborn
  • ETL and data integration
  • Statistical analysis
  • Predictive modeling
  • Data visualization
  • Data validation and documentation