Data Analyst (TS/SCI, 3 yrs exp)
Reston, VA, USA
Full-time
Clearance: Top Secret/SCIJob DescriptionGather 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
