ZipRecruiter

Log In

1

Data Interpretation Jobs (NOW HIRING)

dunnhumby

Senior Applied Data Scientist

Cincinnati, OH · On-site +1

Data Interpretation and Insight Analysis; performing data interpretation, insight generation, and analytical analysis to support business and technical decision-making; * Programming experience on ...

SOSi

Data Analyst

El Paso, TX · On-site

The analyst will be responsible for collecting, analyzing, and interpreting large sets of data from a variety of public, proprietary, and commercial sources to support internal investigations, due ...

SOSi

Data Analyst

El Paso, TX · On-site

The analyst will be responsible for collecting, analyzing, and interpreting large sets of data from a variety of public, proprietary, and commercial sources to support internal investigations, due ...

E-Solutions

Reporting Data Analyst

Chicago, IL · Hybrid

This role serves as a subject matter expert (SME) on enterprise data warehouse content and key source systems, ensuring accurate interpretation of insurance data, consistent definitions, and reliable ...

Prosum Inc.

Functional Data Scientist

Chandler, AZ · On-site

$85 - $100/hr

Instead, it focuses on data interpretation, decision frameworks, and cross-functional collaboration to improve AI system performance. Key Responsibilities * Analyze structured and unstructured ...

Kasmo Global

Telematics/Data Engineer

Mossville, IL · On-site

$83K - $100K/yr

Strong analytical skills for data interpretation, trend analysis, and decision-making. Desired Skills: * Previous experience working with CAT Digital technologies or within the Caterpillar ecosystem.

next page

Showing results 1-20

People also search for

All JobsData Interpretation Jobs

Data Interpretation information

See salary details

$46K

$165K

$243.5K

How much do data interpretation jobs pay per year?

As of Jun 4, 2026, the average yearly pay for data interpretation in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Interpreter, you need strong analytical skills, statistical knowledge, and a solid understanding of data visualization, often supported by a degree in mathematics, statistics, or a related field. Familiarity with tools like Microsoft Excel, Tableau, or Python for data analysis and visualization is typically required. Attention to detail, critical thinking, and the ability to communicate complex findings clearly are valuable soft skills in this role. These skills ensure accurate data-driven insights and effective communication to guide business decisions.

How does a Data Interpretation specialist typically collaborate with cross-functional teams to drive business insights?

Data Interpretation specialists frequently work alongside analysts, business managers, and IT teams to translate raw data into actionable insights. They are responsible for clarifying data trends, ensuring data accuracy, and contextualizing findings for non-technical stakeholders, often presenting results through visualizations or reports. Effective collaboration requires strong communication skills and a good understanding of both business objectives and technical data limitations. This teamwork enables organizations to make informed decisions and continuously improve processes based on data-driven evidence.

What is data interpretation?

Data interpretation is the process of analyzing data sets and extracting meaningful insights or conclusions from them. It involves examining data in various forms, such as tables, charts, and graphs, to identify patterns, trends, and relationships. This skill is essential in many fields, including business, research, and education, as it helps inform decision-making and problem-solving. Effective data interpretation requires critical thinking, attention to detail, and a good understanding of the context in which the data was collected.

What is the difference between Data Interpretation vs Data Analysis?

AspectData InterpretationData Analysis
Primary FocusUnderstanding and explaining data insightsExamining data to identify patterns and trends
Skills RequiredAnalytical thinking, communication, visualizationStatistical skills, programming, data manipulation
Tools UsedCharts, reports, visualization softwareExcel, SQL, Python, R
Work EnvironmentBusiness meetings, reporting, presentationsData warehouses, analysis platforms

Data Interpretation involves explaining what data means and communicating insights, often to non-technical stakeholders. Data Analysis focuses on examining raw data to uncover patterns and trends, often using statistical tools. While both roles require analytical skills, Data Interpretation emphasizes understanding and storytelling, whereas Data Analysis emphasizes technical data manipulation and discovery.

More about Data Interpretation jobs
What are the most commonly searched types of Data Interpretation jobs? The most popular types of Data Interpretation jobs are:
What states have the most Data Interpretation jobs? States with the most job openings for Data Interpretation jobs include:
What job categories do people searching Data Interpretation jobs look for? The top searched job categories for Data Interpretation jobs are:
Data Interpretation jobs near you

Senior Applied Data Scientist

dunnhumby

Cincinnati, OH • On-site, Remote

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail - one of the world's most competitive markets, with a deluge of multi-dimensional data - dunnhumby today enables businesses all over the world, across industries, to be Customer First.

Job Title: Senior Applied Data Scientist

Job Location: 3825 Edwards Road, #600, Cincinnati, OH 45209 (May work remotely)

Job Duties:

WHY I DO MY JOB | Job purpose

To lead and execute projects to distil complex problems into compelling insights, using the best of dunnhumby science and making recommendations that resonate with clients and lead them to action. May telecommute 100% of the time from their home office, consistent with dunnhumby's remote work policy.

WHAT I DO | Key accountabilities

  • Build strong relationships with internal contacts & external clients to ensure full understanding of client challenges, growth strategy and agreed measures of success for the project.
  • Investigate and implement the most appropriate analytical technique for each project, role modelling the re-use & further development of global solutions or code written by others.
  • Deploy data science algorithms and market products on chosen tech stack for efficient and cost-effective delivery.
  • Identify opportunities to grow client engagement by proactively solving client's strategic questions, using a mix of products and advanced data science techniques that support executive decision making and calls to action.
  • Participate in client meetings as required to present methodology and solutions through effective story telling techniques.
  • Work closely with global products team to provide market feedback for enhancing an existing product offering or augmenting the catalogue with a market-based product that can become global offering.
  • Ensure smooth running of your data analytics projects and support junior team members with their projects.
  • Lead by example by following dunnhumby Quality Assurance processes, ways of working and coding standards.
  • Provide advice and support to colleagues to resolve challenges and support code reviews.

Job requirements:

  • Bachelor's degree (or foreign educational equivalent) in Computer Science, Mathematics, Applied Statistics, Engineering or related field.
  • In addition to the degree, must have at least 4 years of experience in each of the following:
  • Software development, utilizing methodologies and tools such as Agile (Scrum Master) and Code Merge, and programming in languages including PySpark, Python, Flask/Dash, C++, and HTML; and
  • Quality Assurance (QA) and Testing, including the development, execution, and maintenance of automated and manual testing frameworks.

Within this, must have at least 2 years of experience in each of the following:

  • Handling large data volumes with modern data processing tools, e.g. by using Hadoop, Spark, SQL, and Python;
  • Data Interpretation and Insight Analysis; performing data interpretation, insight generation, and analytical analysis to support business and technical decision-making;
  • Programming experience on any standard data mining and modelling packages such as Python and R; and
  • Applying advanced statistical models and machine learning algorithms to develop and implement solutions to complex analytical and business problems.

Apply