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Data Science Visualization Jobs in Indiana (NOW HIRING)

Eightelevengroup

Sr. Data Scientist

Indianapolis, IN · On-site

$110.21 - $121.23/hr

... visualization--and collaborate closely with engineering and product teams to embed spatial ... in data science, GIS, or a related field * Strong proficiency in Python for geospatial data ...

Elevance Health

Data Scientist

Indianapolis, IN · Hybrid

Developing and maintaining data science models, detection analytics, and behavioral algorithms for ... Data visualization and dashboard development experience preferred. * Big data technologies ...

Elevance Health

Data Scientist

Indianapolis, IN · Hybrid

Developing and maintaining data science models, detection analytics, and behavioral algorithms for ... Data visualization and dashboard development experience preferred. * Big data technologies ...

Haynes International

Data Analytics Engineer

Kokomo, IN · On-site

$101K - $121K/yr

A bachelor's degree in computer science, data science, software engineering, or related field (R ... Familiarity with data visualization tools such as Targit & Power BI; Knowledge of upgrading data ...

JCD Staffing

UI/UX SME

Crane, IN · On-site +1

$185K/yr

Support data science initiatives through visualization, analytics tools, and interface design * Contribute to system and data architecture planning for scalable CBM+ solutions * Ensure interfaces are ...

RADcube - A NLogix Company

Data Analyst

Indianapolis, IN · On-site

$70 - $110/hr

... Science, Business Analytics, or related), or equivalent practical experience Preferred Qualifications Experience with BI/visualization tools Exposure to Delta Lake, Snowflake, or similar modern data ...

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Data Science Visualization information

What is data science visualization?

Data Science Visualization refers to the practice of creating graphical representations of data and analytical results to make complex information more understandable and actionable. Data visualization helps data scientists communicate insights, identify patterns, and inform decision-making by presenting data in charts, graphs, maps, and interactive dashboards. It bridges the gap between technical analyses and non-technical stakeholders, enabling clearer communication and more effective storytelling with data.

How does a data science visualization specialist typically collaborate with data scientists and other stakeholders during a project?

Data Science Visualization specialists play a key role in bridging the gap between complex data analysis and actionable insights. They often work closely with data scientists to understand the underlying data models and results, and then collaborate with business stakeholders to ensure visualizations are tailored to the audience's needs. Regular meetings, feedback sessions, and iterative design processes are common, enabling effective communication and ensuring that visual outputs are both accurate and impactful. This collaborative environment helps ensure that data-driven insights are easily understood and used for decision-making across the organization.

What are the key skills and qualifications needed to thrive as a data science visualization specialist, and why are they important?

To thrive in Data Science Visualization, you need a strong grasp of data analysis, statistics, and data storytelling, often supported by a degree in computer science, statistics, or a related field. Proficiency with visualization tools like Tableau, Power BI, or D3.js as well as programming languages such as Python or R is typically required. Creativity, attention to detail, and effective communication are valuable soft skills for translating complex data into clear, actionable visuals. These skills are crucial for transforming raw data into insights that drive informed business decisions.

What is the difference between Data Science Visualization vs Data Analyst?

AspectData Science VisualizationData Analyst
Required SkillsData visualization tools, programming (Python, R), statistical knowledgeExcel, SQL, basic statistics, data reporting
Work EnvironmentData science teams, research projects, advanced analyticsBusiness units, reporting, data cleaning
Industry UsageTech, finance, healthcare, researchRetail, marketing, finance, operations

Data Science Visualization focuses on creating advanced visual representations of complex data sets using programming and statistical tools, often within data science teams. Data Analysts primarily generate reports and dashboards using tools like Excel and SQL for business decision-making. While both roles involve data visualization, Data Science Visualization emphasizes technical, programming-based visualizations for in-depth analysis, whereas Data Analysts focus on accessible reports for business insights.

What are popular job titles related to Data Science Visualization jobs in Indiana?

For Data Science Visualization jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Data Science Visualization jobs in Indiana look for?

The top searched job categories for Data Science Visualization jobs in Indiana are:

What cities in Indiana are hiring for Data Science Visualization jobs?

Cities in Indiana with the most Data Science Visualization job openings:

Data Science Visualization jobs near you

Sr. Data Scientist

Eightelevengroup

Indianapolis, IN • On-site

$110.21 - $121.23/hr

Other

Posted 28 days ago

Job description

Geospatial Data Scientist

Remote

This is a Remote role.

Compensation: $80 - $88 per hour

ABOUT THE ROLE

Our client is seeking a Geospatial Data Scientist to transform complex spatial data into actionable insights and support product and business decision-making. In this role, you will work across the full geospatial data pipeline—from data ingestion and processing to analysis, modeling, and visualization—and collaborate closely with engineering and product teams to embed spatial intelligence into our platform. You will be responsible for developing and maintaining spatial data models, applying machine learning techniques to spatial problems, and creating compelling visualizations for diverse stakeholders. The ideal candidate thrives in a fully remote, asynchronous environment and brings a solid understanding of geospatial standards, coordinate reference systems, and data quality management.

WHAT YOU'LL DO
  • Design and execute geospatial analyses to support product and business decision-making
  • Build, validate, and maintain spatial data models and pipelines
  • Query and manage geospatial datasets using PostgreSQL with PostGIS
  • Work with geospatial data formats including GeoJSON, Shapefile, GeoTIFF, WKT, and WKB
  • Develop machine learning models with spatial components (clustering, classification, interpolation, etc.)
  • Create maps, dashboards, and visualizations to communicate findings to technical and non-technical stakeholders
  • Collaborate with backend engineers to integrate geospatial features into production systems
  • Evaluate and maintain geospatial data quality, coverage, and accuracy
  • Apply GIS tools (QGIS, ArcGIS, or equivalent) for spatial analysis and visualization
  • Ensure clear communication of geospatial insights in a remote, async environment
  • Maintain familiarity with geospatial standards, coordinate reference systems, and spatial indexing
  • Contribute to spatial data infrastructure and cloud-native geospatial workflows as needed
WHAT YOU BRING
  • 3–6 years of experience in data science, GIS, or a related field
  • Strong proficiency in Python for geospatial data analysis and modeling (GeoPandas, Shapely, Fiona, Rasterio, or similar)
  • Deep experience with PostgreSQL and PostGIS for spatial querying and data management
  • Familiarity with geospatial standards and formats (GeoJSON, Shapefile, GeoTIFF, WMS/WFS, WKT, WKB, etc.)
  • Experience with GIS tools such as QGIS, ArcGIS, or equivalent
  • Solid understanding of coordinate reference systems (CRS), projections, and spatial indexing
  • Experience applying machine learning techniques to spatial problems
  • Ability to communicate findings clearly in a fully remote, async environment
  • Experience with remote sensing or satellite imagery analysis (nice to have)
  • Familiarity with cloud-native geospatial tools (PostGIS on AWS RDS, Google Earth Engine, etc.) (nice to have)
  • Exposure to spatial data infrastructure (GeoServer, MapServer, Mapbox, Deck.gl) (nice to have)
  • Experience with big geospatial data processing (Apache Sedona, H3, S2) (nice to have)
  • Knowledge of Docker and containerized data workflows (nice to have)
  • Familiarity with CI/CD and version control best practices (nice to have)
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