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Data Analyst Computer Science Jobs in Indiana (NOW HIRING)

STI

Data Analyst

Indianapolis, IN · On-site

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field. Proficiency in data analysis tools such as SQL, Python, R, or Excel. Experience with data visualization ...

Staffingine LLC

DWD - Data Analyst

Indianapolis, IN · On-site

Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field. * Proficiency in data analysis tools such as SQL, Python, R, or Excel. * Experience with data ...

RushShelby Energy

Process & Data Analyst

Manilla, IN · On-site

Data Analytics, Statistics, Computer Science, Computer Engineering, Business, or related field) required * 3+ years of experience in data analysis, business intelligence, or related role, preferred ...

Harrison Steel Castings Co.

Data Analyst

Attica, IN · On-site

Ability to read, analyze, and interpret common scientific and technical journals, financial reports ... Computer Skills: Advanced working knowledge of Microsoft Office Suite required. Certificates and ...

Harrison Steel Castings Co.

Data Analyst

Attica, IN · On-site

Ability to read, analyze, and interpret common scientific and technical journals, financial reports ... Computer Skills: Advanced working knowledge of Microsoft Office Suite required. Certificates and ...

Harrison Steel Castings Co.

Data Analyst

Attica, IN

Ability to read, analyze, and interpret common scientific and technical journals, financial reports ... Computer Skills: Advanced working knowledge of Microsoft Office Suite required. Certificates and ...

OrganOx

Senior Data Quality Analyst

Indianapolis, IN · On-site +1

Bachelor's Degree in an analytical/research field (Math, Physics, Engineering, Computer Science, Statistics, etc.) and 5+ years of experience in data analytics, or equivalent combination. Advanced ...

Interra Credit Union

Senior Data Analyst

Goshen, IN

$76K - $96K/yr

Education / Certifications / Licenses This level of knowledge is normally acquired through completion of a Bachelor's degree in Data Analytics, Statistics, Computer Science, Information Systems ...

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Data Analyst Computer Science information

Is 40 too late for data science?

Data analysts and data scientists can successfully transition into the field at age 40 or older, as skills in programming, statistics, and data visualization are valuable regardless of age. Many professionals acquire relevant certifications or learn tools like Python, R, or SQL later in their careers to enhance their prospects.

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

To thrive as a Data Analyst in Computer Science, you need strong analytical skills, proficiency in statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with data analysis tools such as SQL, Python, R, and data visualization platforms like Tableau or Power BI, as well as experience with database systems, are typically required. Attention to detail, problem-solving abilities, and effective communication help data analysts translate complex data into actionable insights for stakeholders. These skills are crucial for accurately interpreting data trends, supporting business decisions, and driving organizational growth.

What is a Data Analyst in Computer Science?

A Data Analyst in Computer Science is a professional who collects, processes, and analyzes data to help organizations make informed decisions. They use various statistical tools and programming languages, such as Python, R, and SQL, to interpret complex datasets and identify trends or patterns. Their work often involves cleaning data, creating visualizations, and preparing reports for stakeholders. Data Analysts play a key role in turning raw data into actionable insights that drive business strategies.

How does a Data Analyst with a computer science background typically collaborate with other departments within a company?

Data Analysts with a computer science background often work closely with teams such as marketing, product development, and IT to translate raw data into actionable insights. They may participate in cross-functional meetings to understand business goals, provide data-driven recommendations, and help automate data collection processes. Strong communication skills are essential, as analysts must explain technical findings in a way that non-technical stakeholders can understand. This collaborative environment not only broadens their impact but also exposes them to various aspects of the business, fostering professional growth.

Can I be a data analyst with computer science?

Yes, a background in computer science provides a strong foundation for a data analyst role, as it covers programming, data structures, and algorithms. Data analysts often use tools like SQL, Excel, and statistical software, and having programming skills in languages such as Python or R is highly beneficial.

Is a data analyst a high salary?

Data analysts typically earn competitive salaries that vary based on experience, location, and industry. In general, they have higher-than-average starting pay compared to many entry-level roles, especially when skilled in tools like Excel, SQL, and data visualization software. Advanced skills or certifications can lead to higher compensation.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication, which are difficult for AI to fully replicate. Therefore, AI is more likely to augment rather than replace data analysts in the foreseeable future.
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Data Analyst Computer Science jobs near you

Data Analyst

STI

Indianapolis, IN • On-site

Full-time

Re-posted 15 days ago

Job description

Data Analyst is responsible for collecting, processing, and analyzing data to help make data-driven decisions. This role involves working with large datasets, identifying trends, creating reports, and providing actionable insights to stakeholders.
Job Summary:
The Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make data-driven decisions. This role involves working with large datasets, identifying trends, creating reports, and providing actionable insights to stakeholders.
Key Responsibilities:
Gather, clean, and organize large datasets from various sources.
Validate and verify data accuracy, consistency, and completeness across various data sources.
Identify and resolve data discrepancies, inconsistencies and errors.
Performa routine and ad hoc data quality checks using automated and manual validation techniques.
Work closely with data entry teams and other analysts and stakeholders to ensure data integrity.
Perform data analysis to identify trends, patterns, and correlations.
Develop reports, dashboards, and visualizations using tools like Excel, SQL, Tableau, or Power BI.
Collaborate with cross-functional teams to support business objectives.
Interpret data to provide strategic recommendations and business insights.
Ensure data accuracy and integrity.
Use statistical techniques and predictive modeling to improve decision-making.
Document processes and methodologies for data collection and analysis.
Required Skills & Qualifications:
Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field.
Proficiency in data analysis tools such as SQL, Python, R, or Excel.
Experience with data visualization tools like Tableau, Power BI, or Google Data Studio.
Strong analytical and problem-solving skills.
Excellent communication and presentation abilities.
Ability to work independently and in a team-oriented environment.
Attention to detail and a strong understanding of data governance principles.
Preferred Qualifications:
Experience in machine learning, predictive modeling, or statistical analysis.
Knowledge of database management and ETL (Extract, Transform, Load) processes.
Familiarity with cloud platforms such as AWS, Google Cloud, or Azure.

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