Senior Data Scientist (TS/SCI)

Location: Hybrid in Ashburn, VA w/telework available

Ninja Analytics is looking for a Senior Data Scientist to help lead the development and delivery of high-quality predictive modelling 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. They will help our team to leverage large structured and unstructured datasets to develop and operationalize models, tools, and applications that drive optimized decision making. Project tasks include data collection, mining, data and text analytics, clustering analysis, pattern recognition and extraction, automated classification and categorization, and entity resolution to implement and enhance automated risk assessment. The products we develop provide actionable insight with real and immediate impact on the safety and security of the United States, its citizens, visitors, and economy.

The strongest applicants will offer multiple years of experience in highly dynamic, threat/risk driven operating environments. They will also have a proven track record of delivering production ready decision support tools and applications employed in the field and by mission-support entities. Applicants will have a demonstrated capacity to work closely and collaboratively with mission stakeholders; respond to emergent, mission-driven changes in priorities and expected outcomes; and apply new and emerging tools and techniques. Within three - six months of joining the project, data scientists will be expected 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 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.

Qualifications

Education:

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

Required Qualifications

12+ years of related 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.
Proficiency with SQL programming
Experience constructing and executing queries to extract data in support of EDA and model development
Proficiency with statistical software packages including: 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

Desired Qualifications

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)

Security Clearance:

Selected applicants must be a US Citizen and able to obtain and maintain a Top Secret Security Clearance

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