DATA ANALYST

Job Overview

⭐ Featured Role | Apply direct with Data Freelance Hub

Contract, hybrid remote in Indianapolis, IN. Pay  38.25– 40.75 per hour.

Location:

Indianapolis, IN 46266. Remote possible.

Job type:
Contract.

Hours:

40 per week. Expiration date:
December 30, 2025.

• Serve as project lead / subject matter expert for specific data sources, as assigned.
• Review and provide feedback on the work products of other analysts.
• Transfer raw data to appropriate location for use in data analysis projects.
• Wrangle, clean, and validate agency data sources with minimal guidance.
• Conduct general analysis of agency datasets; serve as project lead, as assigned.
• Contribute to complex analysis of agency datasets, as requested.
• Conduct data quality checks to ensure validity and cleanliness of agency datasets prior to analysis and reporting.
• Oversee and review projects completed by associate analysts, as requested by senior analyst.
• Interpret data from multiple sources using a variety of analytical techniques, ranging from simple aggregation to data mining and complex statistical methodologies.
• Collaborate with internal and external partners to develop novel ways of using and reporting data.
• Provide technical assistance to program areas for the creation of reports and grant deliverables.

• Demonstrated experience with data queries and transformations (including cleansing and standardizing) with SQL.
• Demonstrated experience with SAS and either R or Python, including data cleaning, running descriptive statistics and full analyses.
• Working knowledge of epidemiological methods, study design, and analysis needed with an understanding of both qualitative and quantitative data.
• Working knowledge of MS Office Suite including Excel, Word, and PowerPoint.
• Effective time management and program management skills.
• Ability to work in a team environment with multiple and fluid demands.
• Ability to maintain effective and professional working relationships with internal and external customers.
• Ability to research and document findings.

• Knowledge of SQL, SAS, R or Python, and epidemiological methods.
• Experience with data cleaning, descriptive statistics, and full analyses.
• Strong analytical and statistical skills.
• Proficiency with MS Office Suite.

• Data Cleaning
• Python
• Datasets
• Data Quality
• R
• Data Aggregation
• ETL (Extract Transform Load)
• SAS
• Data Analysis
• SQL (Structured Query Language)
• Data Mining
• Statistics

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