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Retail Data Analyst Remote Jobs in Tennessee (NOW HIRING)

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Data Analysis: * Collect and analyze data to gain insights into user behaviour, product usage, and marketing performance. * Use data-driven decisions to guide growth strategies and experiments. Viral ...

Compliance Analyst Quorum Health Corporate Office (Remote Position) You must reside in one of these ... Analyze Compliance and Privacy Program data and create reports. * Participate in compliance and ...

Showing results 21-40

Retail Data Analyst Remote information

See Tennessee salary details

$30.9K

$75K

$123.4K

How much do retail data analyst remote jobs pay per year?

As of Aug 9, 2026, the average yearly pay for retail data analyst remote in Tennessee is $75,006.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,700.00 and $88,000.00 per year, depending on experience, location, and employer.

What is a retail data analyst?

A Retail Data Analyst (Remote) is a professional who works from a remote location to collect, analyze, and interpret data related to retail sales, customer behavior, inventory, and market trends. They use statistical tools and software to identify patterns, provide actionable insights, and support decision-making for retail businesses. Their work helps companies optimize pricing, improve inventory management, and enhance customer experiences without being physically present in a traditional office or store. Remote analysts frequently collaborate with teams via digital platforms and must be comfortable working independently while managing deadlines.

What is the difference between Retail Data Analyst Remote vs Retail Business Analyst?

AspectRetail Data Analyst RemoteRetail Business Analyst
Required CredentialsBachelor's in Data Analytics, Statistics, or related field; proficiency in SQL, Excel, data visualization toolsBachelor's in Business, Economics, or related; strong analytical skills, familiarity with retail operations
Work EnvironmentRemote, independent data analysis, reporting, and visualizationOn-site or hybrid, analyzing business processes and strategies
Employer & Industry UsageRetail companies, e-commerce firms, and consulting agenciesRetail chains, merchandising firms, and supply chain companies

The main difference is that Retail Data Analyst Remote focuses on analyzing retail data remotely using technical skills, while Retail Business Analyst emphasizes understanding retail business processes and strategies, often with a broader scope. Both roles require analytical skills but differ in their focus and work environment.

How does a retail data analyst typically collaborate with other departments to drive business decisions?

As a remote Retail Data Analyst, you’ll frequently collaborate with teams such as marketing, merchandising, operations, and IT. Communication is often handled through virtual meetings, shared dashboards, and collaborative platforms to ensure everyone has access to up-to-date insights. You’ll translate data findings into actionable recommendations, help set KPIs, and present your analyses to both technical and non-technical stakeholders. Building strong virtual relationships and clear communication are key to influencing decisions and driving improvements across the retail business.

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

To thrive as a Retail Data Analyst (Remote), you need strong analytical skills, proficiency in statistics, and a degree in data science, business, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), SQL, and advanced Excel, along with experience in retail analytics platforms, is typically required. Attention to detail, problem-solving abilities, and effective remote communication make someone stand out in this position. These skills enable analysts to extract actionable insights from complex retail data, driving strategic decisions and business growth from a remote setting.
What job categories do people searching Retail Data Analyst Remote jobs in Tennessee look for? The top searched job categories for Retail Data Analyst Remote jobs in Tennessee are:
What cities in Tennessee are hiring for Retail Data Analyst Remote jobs? Cities in Tennessee with the most Retail Data Analyst Remote job openings:
Infographic showing various Retail Data Analyst Remote job openings in Tennessee as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $75,006 per year, or $36.1 per hour.

Mgr Marketing Data Science

Federal Express Corporation

Collierville, TN • On-site, Remote

Other

Re-posted 10 days ago


Job description

The primary focus of this position is to lead and manage a team responsible for developing and implementing data science initiatives to drive strategic business outcomes. Building and nurturing a high-performing data science team through hiring, coaching, mentoring, and talent development. Identifying and solving complex business problems using large data and advanced analytics/machine learning techniques. Leading data science/advanced analytics initiatives such as customer data platform optimization, consumer insights modeling, market analytics, forecasting, retail network optimization, pricing analytics, and revenue management modeling. Providing expert guidance to a team of data scientists in the use of machine learning, predictive modeling, quantitative analytics, and applied statistics. Developing new analytical approaches and algorithms to address challenging problems. Delivering bottom-line impact through rapid, agile modeling approaches in collaboration with diverse partners. Establishing best practices for machine learning model development, documentation, deployment, version control, automation, and scalability. Providing expert guidance and thought leadership to business partners and executive leadership on the application of data science methodologies to high-impact business problems. Perform other duties as assigned.


Requirements


Master's degree in data science, analytics, business, computer science, operations research, statistics, applied mathematics, business analytics or related quantitative disciplines plus 5 years of experience in the job offered or 5 years of experience in applying data science, operations research, or data analytics modeling to generate revenue, reduce costs, increase profitability, and improve customer experience required. The employer will alternatively accept a PhD in data science, analytics, business, computer science, operations research, statistics, applied mathematics, business analytics or related quantitative disciplines plus 2 years of experience in the job offered or 2 years of work experience in applying data science, operations research, or data analytics modeling to generate revenue, reduce costs, increase profitability, and improve customer experience required in lieu of a Master's degree plus 5 years of experience.

The position requires experience with: Extensive knowledge in advanced data science/analytics, statistical analysis, and machine learning methods. Experience conducting end-to-end analyses, including data gathering, processing, analysis, and presentation. Strong familiarity with evolving analytics concepts, techniques, and technologies. Ability to lead a technical team. Experience providing leadership in a general planning or consulting setting. Experience as a leader or senior member of multi-functional project teams. Strong human relations, organizational/time management, project management, and software development skills. Excellent interpersonal skills and the ability to present and communicate effectively to executive audiences. Technical background in computer science, engineering, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational fields. Proven track record of data science/data engineer expertise, designing and deploying technical solutions that deliver tangible, ongoing value. Demonstrated ability to deliver projects with a team, often working under tight time constraints to deliver value. An engineering mindset, willing to make rapid, pragmatic decisions to accelerate the delivery of business insights and impact. Demonstrated expertise in working with common programming languages and tools such as Python, Scala, R, SAS, SQL, C++, Java, or other modern programming languages. Experience with diverse machine learning (ML) frameworks. Extensive experience in advanced data science and analytics techniques including Geospatial Analytics, Statistics, Predictive Modeling, and Quantitative Analytics. Strong skills in Machine Learning and ML Engineering techniques to develop and implement ML solutions to complex business problems. Proficiency in programming languages such as Python, PySpark, R, SAS, and SQL for data manipulation, analysis, and model development. Expertise in analytical tools such as SAS, ESRI ArcGIS, Azure Databricks and the Microsoft Azure tech stack. Strong understanding of the retail sector and a deep understanding of consumer behavior in transportation setting. 

Position supervises 6 employees.

Position allows for telecommuting from home within commuting distance of Collierville, TN.