Data Scientist

Job Description

This is a remote position.

We are seeking a Data Scientist to join our team in support of a government customer. This is a hybrid position located in Ashburn, VA.

The Data Scientist will help lead the development and delivery of high-quality predictive modelling solutions.

• Lead and perform hands‑on analysis and modeling involving the creation of intervention hypotheses and experiments, assessment of data needs and available sources, determination of optimal analytical approaches, performance of exploratory data analysis, and feature generation.
• Collaborate with mission stakeholders to define, frame, and scope mission challenges where big data interventions may offer important mitigations and develop robust project plans with key milestones, detailed deliverables, robust work tracking protocols, and risk mitigation strategies.
• 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.
• Brief project management, technical design, and outcomes to both technical and non-technical audiences including senior government stakeholders throughout the model development/ project lifecycle through written as well as in-person reporting.

• Bachelor’s Degree (required) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.

• 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, Power
  
  BI).
• Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, Map Reduce, Spark, Kafka, Sqoop).
• Master’s Degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.
• Active Top Secret clearance.

Selected applicants must be a US Citizen and able to obtain and maintain a government security clearance.