Data Scientist with Security Clearance

The Data Scientist candidate will support a Department of Justice (DOJ) component in discovering and analyzing enterprise-level toolsets that enable the organization to uncover valuable insights hidden in vast amounts of available data. The candidate's primary focus will be on identifying tools for data mining techniques, performing statistical analysis, and building high-quality predictive systems integrated with products. This role is responsible for leveraging big data technologies and applying data science models to analyze large datasets and generate actionable insights. A current Top Secret security clearance is required. Responsibilities include, but are not limited to:
Selecting features, building, and optimizing classifiers using machine learning techniques
Applying state-of-the-art data mining methods
Implementing enhanced data collection procedures to include relevant information for building analytic systems
Processing, cleansing, and verifying the integrity of data used for analysis
Conducting ad-hoc analysis and presenting results clearly
Creating and demonstrating automated anomaly detection systems, along with continuous performance tracking
Designing new approaches to handle, analyze, and utilize large volumes of data
Addressing fundamental issues with data handling, search, and retention
Solving complex data storage and processing challenges
Designing new software solutions to improve data search processes
Analyzing and reporting results with actionable recommendations Required Qualifications and Skills:
A current Top Secret security clearance.
5 years of experience supporting projects of similar size and scope
In-depth understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Proficiency with data science toolkits such as R, Weka, NumPy, and MatLab
Strong communication skills
Experience with data science tools and software, including Microsoft Power BI, Anaconda, and SPSS
Expertise in data visualization tools such as D3.js, GGplot, etc.
Proficiency in SQL and Hive query languages
Experience with NoSQL databases such as MongoDB, Cassandra, and HBase
Strong applied statistics skills, including distributions, statistical testing, and regression analysis
Scripting and programming expertise