Data Scientist
ManTech
- Ashburn, VA
- $90,200-149,600 per year
- Permanent
- Full-time
- Perform hands-on analysis and modeling with large, complex data sets to provide solutions to support a wide range of law enforcement mission areas.
- Demonstrate proficiency in extracting, cleaning, and transforming CBP transactional and mission data associated within an identified problem space to build predictive models as well as develop appropriate supporting documentation.
- Leverage knowledge of a variety of statistical and machine learning techniques and methods to define and develop programming algorithms; train, evaluate, and deploy predictive analytics models that directly inform mission decisions.
- Execute projects including those intended to identify patterns and/or anomalies in large datasets; perform automated text/data classification and categorization as well as entity recognition, resolution and extraction; and named entity matching
- Bachelor’s Degree (required) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.
- Experience in developing machine learning models and applying advanced analytics solutions to solve complex business problems
- Experience with programming languages including: R, Python, Scala, Java.
- Experience with SQL programming
- Experience constructing and executing queries to extract data in support of EDA and model development
- Experience with pattern recognition and extraction, automated classification, and categorization
- Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/ disambiguation)
- Experience with unsupervised and supervised machine learning techniques and methods
- Experience performing data mining, analysis, and training set construction
- Proficiency with statistical software packages including: SAS, SPSS Modeler, R, WEKA, or equivalent
- Proficiency with Unsupervised Machine Learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc.
- Proficiency with Supervised Machine Learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc.
- Experience with pattern recognition and extraction, automated classification, and categorization
- Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/ disambiguation)
- Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI)
- Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop)
- Master’s Degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience
- Selected applicants must be a US Citizen and able to obtain and maintain a U.S. Customs and Border Protection (CBP) suitability.