The data scientist will utilize their expertise in machine learning, statistical data analytics, and predictive analytics to help implement analytics tied to cyber security and hunting methodologies and applications.
In this role, the selected candidate will apply knowledge of machine learning techniques and concepts, including the design and implementation of advanced artificial intelligence, computational algorithms, and data science techniques. Develop applications using Python and C++ or Java.
In this role, you will develop next generation search capabilities for our government client, optimizing discover ability of billions of records across disparate data sets in a highly salable environment.
Candidate is expected to conduct experiments, investigations, observations and related research studies into the nature and operation of natural phenomena in a particular field, using the scientific method. They will develop theories for understanding, characterizing and organizing natural phenomena into a systematic and meaningful pattern for the benefit of project advancement and emerging technologies.
In this role, the selected candidate will plan, conduct, and coordinate the development of complex and diverse scientific computer programs, associated documentation, block diagrams, and logic flow charts and provide technical advice and consultation on difficult scientific programming applications to other staff members.
The candidate will support companys FAA work program by performing data analysis and data processing using a broad spectrum of tools and technologies to meet both internal analysis and external client requirements.
Analyzes data to describe client behavior and preferences, understand channel usage, diagnose client experience problems, size marketing opportunity, target clients for treatment and measure the impact of marketing and servicing initiatives.
Designing and building algorithms and predictive models using techniques such as linear and logistic regression, support vector machines, ensemble models (random forest and/or gradient boosted trees), neural networks, and clustering techniques.