Leidos Corporate IT Services Group has an immediate need for a Data Science Analyst in Orlando, FL. In this role, you will support enterprise analytics teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Bachelor's degree in Statistics, Mathematics, Computer Science or another quantitative field.
- Minimum 4 years of experience related to data management and analysis, which includes experience in manipulating data sets and building statistical models.
- Experience with distributed data / computing tools: Map/Reduce, Hadoop, Hive, Spark, etc.
- Strong experience using a variety of data mining / data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
- Proven ability to drive business results with their data-based insights. Must be comfortable working with a wide range of stake holders and functional teams.
- Experience visualizing/presenting data for stakeholders using Oracle Analytics, Cognos Analytics, Tableau, etc.
- Experience using statistical computer languages (R, Python, SQL, etc) to manipulate data and draw insights from large data sets.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc) and experience with applications.