Data Exploration and Testing Lead
Headquarters: Fairfax, VA
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The Federal Energy, Environment and Commerce Operation of Leidos is seeking a Data Exploration and Testing Lead for our Fairfax, VA location, contingent upon award. The job of the Data Exploration and Testing Lead is to perform in a demanding, high-energy position requiring flexibility and innovative technical solutions to the challenges of processing, interpreting, analyzing, and performing inference over large volumes of heterogeneous data, including text, images and other media. We are seeking individuals with a unique blend of research and operational experience, in order to test the application of machine learning models and graph analytic approaches to diverse problems in complex environments. The candidate will support the testing of initial hypothesis validation in an iterative process. Leadership in operational implementation and transition is required. This candidate will provide direction and project leadership, test innovative concepts for further exploration, and implement solutions that extend capability for our customers.
The ideal candidate will be able to independently design and undertake new research as well as partner in a team environment across organizations. Develop topic descriptions for creative and innovative approaches to solving challenges. Provide leadership, organization, and technical direction to other team members. Design and implement secure, scalable, graph-based, and fault-tolerant solutions across a distributed architecture, with the objective of researching and developing semi- and fully automated approaches applicable across multiple domains.
The individual selected to this position must successfully complete a security investigation by the government. All tax obligations must be current.
- BA/BS or equivalent experience and 12+ years of prior relevant experience or Masters with 10+ years of prior relevant experience.
- Specialized experience innovating analytical techniques and performing analytical functions using machine-learning libraries and approaches.
- Proven testing experience validating analytical techniques, models, and implementations.
- Strong data analysis skills using R or a comparable platform, and one programming language, e.g. Python, Perl, C/C++, Java.
- Ability to create and maintain productive relationships with customers and stakeholders.
- Excellent design and delivery capabilities with proficiency in gathering requirements and translating business requirements into technical specification.
- 5+ years related work experience in Analytics, Predictive Modeling and/or Database Marketing.
- Strong record of publication in Machine Learning, Artificial Intelligence, or related discipline.
- Undergraduate and/or Masters degree in analytics, finance, computer science, management information systems or business.
- Familiarity with multiple approaches to representing and developing solutions using probabilistic graphical models (Bayes Nets, CRFs, MLNs, PSL) using techniques like statistical relational learning for problems such as causal discovery, temporal dependence, structure mapping and link/evidence prediction.
- Familiarity with multiple state of the art approaches to machine learning (unsupervised, semi-supervised, supervised, transfer) and existing libraries for implementing these approaches (e.g., CUDA, Caffe, Theano, Torch, Nvidia Digits)
- Prior experience with a few of the following models: Logistic Regression, Linear Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Markov Logic Nets, Probabilistic Soft Logic