Data Analyst; TS/SCI
Listed on 2026-01-10
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IT/Tech
Data Analyst, Data Engineer, Data Science Manager, Data Scientist
Data Analyst (TS/SCI, 3 yrs exp)
Reston, VA, USA
Full-time
Clearance:
Top Secret/SCI
Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.
Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining the quality of data in a spreadsheet or through a programming language so that your interpretations won’t be wrong or skewed.
Model data: This entails creating and designing the structures of a database. You might choose what types of data to store and collect, establish how data categories are related to each other, and work through how the data appears.
Interpret data: Interpreting data will involve finding patterns or trends in data that will help you answer the question at hand.
Present: Communicating the results of your findings will be a key part of your job. You do this by putting together visualizations like charts and graphs, writing reports, and presenting information to interested parties.
Qualifications- Bachelors Degree and AND;
- 3 years of relevant experience.
- Critical thinking:
Capable of making assessments or drawing conclusions based on analysis of facts, trends and evidence. - Communication:
Strong written and speaking skills to communicate with colleagues and other stakeholders are good assets in data analysts. - Experience with:
Tableau, Jupyter Notebook and/or SQL.
Desired
Qualifications:
- Programming languages:
Knowing a statistical programming language like Python to enable handling large sets of data and performing complex equations. - Data visualization:
Capable of consolidating findings in a clear, comprehensive format to ensure colleagues, employers, and stakeholders will understand. - Experience with:
Excel, Google Sheets, R or Python, SAS, or Microsoft Power BI all a plus. - Research:
Capable of conducting thorough research to justify trends and anomalies within data. - Statistics and math:
Capable of using statistics and math to validate findings.
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