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).
Demonstrate proficiency in extracting, cleaning, and transforming data associated within an identified problem space to build predictive models as well as develop appropriate supporting documentation.
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.
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
Proficiency with statistical software packages such as: SAS, SPSS Modeler, R, WEKA, or equivalent
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
10+years and Bachelor’s Degree in mathematics, statistics, computer science/engineering, or other related technical fields and/or requilvant years of expereince and education
Active TS/SCI clearance and ability to obtain CI Poly
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 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)
Experience working with large-scale (e.g., terabyte and petabyte) unstructured and structured data sets and databases
We are GDIT. The people supporting some of the most complex government, defense, and intelligence projects across the country. We deliver. Bringing the expertise needed to understand and advance critical missions. We transform. Shifting the ways clients invest in, integrate, and innovate technology solutions. We ensure today is safe and tomorrow is smarter. We are there. On the ground, beside our clients, in the lab, and everywhere in between. Offering the technology transformations, strategy, and mission services needed to get the job done.
GDIT is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status, or any other protected class.