Applied Data Scientist Internship (DoW SkillBridge)

IntelliGenesis•Columbia, MD

1d•Onsite

About The Position

The DoW SkillBridge Program is an opportunity for service members to gain valuable civilian work experience through specific industry training, apprenticeships, or internships during the last 180 days of military service. DoW SkillBridge connects transitioning service members with industry partners in real-world job experiences. Service members participating in DoW SkillBridge programs continue receiving their military compensation and benefits, while industry partners provide the civilian training and work experience. More information can be found here: https://skillbridge.osd.mil/index.htm

Requirements

Must be a U.S. Citizen
Active TS/SCI clearance with polygraph required
Must be able to report daily to Columbia, MD office
Minimum of six (6) years of experience performing data-analysis on collected information to pinpoint unique insight and intelligence opportunities within the data
Experience within at least two (2) of the following skill areas: Mathematics/Statistics, Computer Science, Scripting, Cloud Computing, Data Mining, Metadata Analysis or Machine Learning, Artificial Intelligence, Data Visualization or Data Automation, Data science, Advanced analytical algorithms, Statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models), Data management (e.g., data cleaning and transformation), Data modeling and assessment, Artificial intelligence, Software engineering
Experience constructing and performing complex database search queries
Experience/knowledge of computer science concepts

Nice To Haves

Experience or familiarity with data analytics and/or the following advanced scripting languages and tools: Python, SQL, Jupyter, Pig, ELK Stack, Splunk, PowerBI, Jupyter Notebooks

Responsibilities

Performing data-analysis on collected information to pinpoint unique insight and intelligence opportunities within the data.
Constructing and performing complex database search queries.
Applying advanced analytical algorithms.
Performing statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models).
Managing data (e.g., data cleaning and transformation).
Data modeling and assessment.
Utilizing artificial intelligence.
Applying computer science concepts.