Senior Data Scientist / Machine Learning engineering to identify, propose, develop, verify, and implement mathematical inference models to create radio spectrum awareness for near-real time characterization of radio environments including the detection of anomalies, and the prediction of events. Experience with radio frequency engineering, radio network engineering and cellular communication protocols, and digital signal processing is strongly desired.
Regular activities would include:
Develop and test mathematical models in support of customer-specific applications such as critical asset protection and wireless network monitoring.
Identify internal and external data sources to satisfy model input.
Develop requirements for hardware and software teams for new data sources and features.
Collaborate with system architects to design, implement, and optimize data pipelines.
Collaborate with data visualization personnel to support customer reporting efforts.
Support peer groups with model and algorithm development to solve new challenges and incorporate learning systems into system architecture.
Creating, validating, and deploying models to predict solution to problems with incomplete observable spaces.
Education: MS in statistical signal processing, statistical inference or related areas, statistical control theory; Ph.D. in these areas is advantageous.
5 to 10 years experience in statistical signal processing, machine learning, statistical inference or related areas.
Familiarity with RF communications concepts and RF frequency and band assignments
Knowledge of tools and languages such as MATLAB, python (TensorFlow, NumPy, SciKit-Learn, SciPy), SQL (PostgreSQL, MySQL, NoSQL), Tableau, GIS (ESRI, QGIS, MapInfo), R.
Good communicator able to clearly convey ideas to others and report approach and conclusions to new problems
Send your resume and cover letter to the address below:
Digital Global Systems
7950 Jones Branch Drive, Studio 1A
Tysons, VA 22102
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