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Data Jobs in Kokomo, IN (NOW HIRING)

ClinLab Solutions Group

Scientific Data Architect

Marion, IN · On-site

$54 - $69.50/hr

Scientific Data Architect Work Location: Marion County, Indiana DOES OFFER RELOCATION Summary: Seeking a Scientific Data Architect to drive the design and implementation of advanced scientific data ...

RDSolutions

Data Scanning Associate - 53778

Tipton, IN · On-site

$12 - $18/hr

If you are the type of person who is self-motivated, enjoys working independently, data entry and checking products, then you are the person we are looking for! What does RDSolutions Offer You? * A ...

RDSolutions

Data Scanning Associate - 57103

Kokomo, IN · On-site

$12 - $18/hr

If you are the type of person who is self-motivated, enjoys working independently, data entry and checking products, then you are the person we are looking for! What does RDSolutions Offer You? * A ...

RDSolutions

Data Scanning Associate - 57727

Marion, IN · On-site

$12 - $18/hr

RDSolutions's track record spans nearly 40 years in providing retail data and intelligent solutions for virtually every major North American retailer. Equal Employment Opportunity Statement:

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Data information

See Kokomo, IN salary details

$41.8K

$149.8K

$221.1K

How much do data jobs pay per year?

As of May 28, 2026, the average yearly pay for data in Kokomo, IN is $149,817.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,200.00 and $154,300.00 per year, depending on experience, location, and employer.

What Are Different Jobs That Work With Data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a Data Analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

What are data jobs?

Data jobs refer to roles that involve collecting, processing, analyzing, and interpreting data to support business decisions or research. These jobs can include positions such as data analyst, data scientist, data engineer, and database administrator. Professionals in this field use statistical techniques, programming, and data visualization tools to derive insights from large datasets. Data jobs are in high demand across various industries, including finance, healthcare, technology, and marketing.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

More about Data jobs
What cities near Kokomo, IN are hiring for Data jobs? Cities near Kokomo, IN with the most Data job openings:
Data jobs near you

Scientific Data Architect

ClinLab Solutions Group

Marion, IN • On-site

$54 - $69.50/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Scientific Data Architect

Work Location: Marion County, Indiana

DOES OFFER RELOCATION

Summary:

Seeking a Scientific Data Architect to drive the design and implementation of advanced scientific data solutions. This role focuses on transforming complex scientific data into actionable insights, collaborating with cross-functional teams, and leveraging AI/ML methodologies to accelerate scientific outcomes. The ideal candidate is a proactive problem-solver with deep experience in life sciences, data modeling, and cloud-based product development.

Responsibilities:

  • Engage directly with scientific stakeholders to understand data challenges and requirements, building strong relationships and accelerating tailored solutions.
  • Design and implement scalable, reusable data models to efficiently organize scientific data for diverse use cases.
  • Translate scientific workflows into robust, cloud-based solutions using advanced data platforms and tools.
  • Prototype and implement solutions including data model design (tabular & JSON), Python-based parser development, and lab software integration via APIs.
  • Develop data visualization and applications in Python, utilizing frameworks such as Streamlit and plotting tools like holoviews and Plotly.
  • Collaborate with business analysts, scientists, and AI engineers to develop and deploy machine learning, AI, mechanistic, statistical, and hybrid models.
  • Iterate dynamically with end users and technical stakeholders, driving solution adoption through regular demos, meetings, and proactive communication.
  • Rapidly learn and apply new technologies to troubleshoot and develop scientific use cases, while contributing to product roadmap prioritization based on user feedback.

Qualifications:

  • PhD with 7+ years or Master's with 10+ years of industry experience in life sciences, with extensive domain knowledge in drug discovery, preclinical development, CMC, or product quality testing.
  • Proven experience defining, designing, prototyping, and implementing AI/ML-driven use cases in cloud environments.
  • Strong background collaborating with cross-functional teams, including product managers, engineers, and scientific stakeholders.
  • Expertise in exploratory data analysis and workflow optimization to enable novel scientific outcomes.
  • Excellent communication and storytelling skills, with the ability to engage audiences ranging from scientists to executive stakeholders.
  • Consulting experience advising scientists to advance research, development, and quality testing outcomes.
  • Hands-on experience with Python, data modeling (tabular & JSON), API integration, and scientific application development.
  • Demonstrated ability to rapidly learn new tools, technologies, and scientific domains.
  • Strong ownership mentality and a track record of building extensible data models and applications for scientific end users.

Apply