Senior Data Scientist (TS/SCI)

Ninja Analytics, Inc.; Ashburn (VA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Ninja Analytics, Inc. in Ashburn, VA seeks a Senior Data Scientist (TS/SCI) to lead predictive modeling and analytics for national security challenges. Hybrid work with telework options, focusing on production-ready decision support tools.

Requires 12+ years of experience, ML/AI expertise, and strong skills in Python/R/SQL to analyze large datasets, develop models, and enable mission-driven decisions.

Qualifications

• 12+ years of related experience in data science or analytics.
• Experience in developing machine learning models and applying analytics to complex problems.
• Proficiency with programming languages including R, Python, Scala, Java.

Responsibilities

• Perform hands-on analysis and modeling, create hypotheses, assess data needs, and generate features.
• Collaborate with mission stakeholders to define challenges, scope projects, and set milestones with risk mitigation.
• Demonstrate proficiency in data cleaning, transformation, and building predictive models with supporting documentation.
• Leverage ML techniques to train, evaluate, and deploy analytics models informing mission decisions.
• Execute projects identifying patterns in large datasets, including text classification and entity recognition.
• Brief management and technical outcomes to stakeholders through written and in-person reporting.

Skills

12+ years experience

ML/AI expertise

SQL proficiency

Python/R/Scala

Education

Bachelor's degree

Master's or Ph.D. preferred

Tools

SAS

SPSS Modeler

WEKA

Hadoop/Spark

Job description

Senior Data Scientist (TS/SCI)

Location: Hybrid inAshburn, VA w/telework available

Ninja Analytics is looking for a Senior Data Scientistto help leadthe development and delivery of high-quality predictive modellingsolutions. Successful applicants will serve as recognized subjectmatter experts in the application of quantitative methods, machinelearning algorithms, and predictive models to address complex nationaland homeland security challenges. They will help our team to leveragelarge structured and unstructured datasets to develop and operationalizemodels, tools, and applications that drive optimized decision making.Project tasks include data collection, mining, data and text analytics,clustering analysis, pattern recognition and extraction, automatedclassification and categorization, and entity resolution to implementand enhance automated risk assessment. The products we develop provideactionable insight with real and immediate impact on the safety andsecurity of the United States, its citizens, visitors, and economy.

The strongest applicants will offer multiple years of experience inhighly dynamic, threat/risk driven operating environments. They willalso have a proven track record of delivering production ready decisionsupport tools and applications employed in the field and bymission-support entities. Applicants will have a demonstrated capacityto work closely and collaboratively with mission stakeholders; respondto emergent, mission-driven changes in priorities and expected outcomes;and apply new and emerging tools and techniques. Within three - sixmonths of joining the project, data scientists will be expected to:

• Perform hands-on analysis and modeling involving the creation ofintervention hypotheses and experiments, assessment of data needs andavailable 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 scopemission challenges where big data interventions may offer importantmitigations and develop robust project plans with key milestones,detailed deliverables, robust work tracking protocols, and riskmitigation strategies.
• Demonstrate proficiency in extracting, cleaning, and transformingCBP transactional and mission data associated within an identifiedproblem space to build predictive models as well as develop appropriatesupporting documentation.
• Leverage knowledge of a variety of statistical and machine learningtechniques and methods to define and develop programming algorithms;train, evaluate, and deploy predictive analytics models that directlyinform mission decisions.
• Execute projects including those intended to identify patternsand/or anomalies in large datasets; perform automated text/dataclassification and categorization as well as entity recognition,resolution and extraction; and named entity matching.
• Brief project management, technical design, and outcomes to bothtechnical and non-technical audiences including senior governmentstakeholders throughout the model development/ project lifecycle throughwritten 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 withequivalent 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 includingCluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, DeepBelief Networks, Principal Component Analysis), Segmentation, etc.
• Proficiency with Supervised Machine Learning methods includingDecision 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