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MANTECH

Senior Data Scientist

MANTECH, Washington, District of Columbia, us, 20022

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MANTECH MANTECH

seeks a motivated, career- and customer-oriented

Senior Data Scientist

to join our innovative team in

Washington, DC .

U.S. Immigration and Customs Enforcement (ICE) protects America by enforcing federal laws governing border control, customs, trade, and immigration. Its mission focuses on preserving national security and public safety through criminal investigations and immigration law enforcement. This includes combating transnational crime and identifying, detaining, and removing individuals who violate immigration laws.

In response to this challenge, ManTech, as a trusted mission partner of ICE, seeks capable, qualified, and versatile Senior Data Scientists to help lead the development and delivery of high-quality predictive modeling solutions. Successful applicants will serve as recognized subject matter experts in the application of quantitative methods, machine learning algorithms, and predictive models to address complex national and homeland security challenges.

Responsibilities Include But Are Not Limited To

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 (e.g., identification, derivation, aggregation). 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 ICE 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. Participate in 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.

Minimum Qualifications

7+ years of experience developing and applying machine learning models and advanced analytics to solve complex business problems. Strong foundation in mathematics, statistics, and computer science, typically from an undergraduate degree in a related technical field. Expertise in R, Python, Scala, Java, and SQL for programming and data extraction. Proficient in statistical software packages like SAS, SPSS Modeler, and R. Extensive experience with supervised and unsupervised machine learning techniques, including pattern recognition, classification, clustering, and entity resolution. Bachelor’s degree in mathematics, statistics, computer science/engineering, or other related technical fields

Preferred Qualifications

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. 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 performing data mining, analysis, and training set construction. Experience 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 unsupervised machine learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc.

Clearance Requirements

Must be a U.S. Citizen and be able to obtain and maintain an ICE suitability.

Physical Requirements

The person in this position needs to occasionally move about inside the office to access file cabinets, office machinery, or to communicate with co-workers, management, and customers, which may involve delivering presentations.

Seniority level

Seniority level Mid-Senior level Employment type

Employment type Full-time Job function

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