[Remote] Data Scientist
Note: The job is a remote job and is open to candidates in USA. Knowmadics develops solutions for cybersecurity, space, telecommunications, and other critical infrastructure and security needs. The Data Scientist will work hands-on with engineers, scientists, and human factors professionals to collect data and develop, evaluate, and productionize statistical and machine learning solutions for real-world interdisciplinary problems.
Responsibilities
- Design and develop data collection and experimental protocols to ensure statistically valid, high quality datasets for downstream analysis and model development
- Develop, evaluate, and validate statistical and machine learning models for interdisciplinary problems involving cybersecurity, telecommunications, and sensor data, with an emphasis on spatial, temporal, and spatiotemporal analysis
- Work with human factors specialists, and data/full stack engineers to define system requirements, review developed code, and support translating statistical concepts to coworkers
- Support documentation of analysis results for semi-technical stakeholders
- Occasionally support technical interactions like collaboration, including defining technical requirements for external data collections, and reviewing technical work
Skills
- Graduate-level education (Master's or PhD) in a quantitative field such as natural sciences, mathematics, statistics, economics, psychology, or a related discipline is preferred. Exceptional candidates with a bachelor's degree and substantial applied machine learning or data science experience may also be considered
- 3+ years of professional experience using Python-based scientific computing and machine learning tools (e.g., Numpy, pandas, SciPy, scikit-learn, PyTorch, TensorFlow, PyMC, GeoPandas, etc.)
- 3+ years of experience analyzing complex real-world datasets using statistical inference, predictive modeling, or machine learning techniques
- Experience communicating technical results to semi-technical audience
- Eligible to obtain a U.S. Security Clearance – U.S. Citizenship required
- Experience with Bayesian statistical methods, hierarchical models, Gaussian processes, or probabilistic programming
- Experience with geospatial, temporal, or spatiotemporal statistical analysis
- Exposure to spatial databases and geospatial Python libraries (GeoPandas, Shapely, Rasterio, xarray, PostGIS, etc.)
- Experience with large-scale scientific computing or distributed data processing
- Exposure to deployed analytical or machine learning systems
- Experience developing reproducible analytical workflows and validating statistical models
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