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