Data Scientist

Job Purpose/Summary

Work with our team of engineers, scientists and human factors professionals to develop machine learning and other algorithm data capabilities for cybersecurity, space, and telecommunications. This individual contributor role will involve hands-on work collecting data, developing solutions to real-world problems using machine learning. Developed solutions are actively being productionized to support ongoing cybersecurity initiatives and other crucial infrastructure and security needs.

Duties and 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

Qualifications

• Minimum

  • 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

• Preferred

  • 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

Working conditions

• Employees may be called upon to participate in in-person meetings, trainings, or company functions at Knowmadics offices or other designated locations. Travel in support of business operations may also be required, and employees are expected to comply with these obligations as part of their position.

• Candidate should live within driving distance of the following areas: Wichita, KS;  Lawton OK; or Round Rock, TX

• Some weekend work may be required based on project deadlines or operational needs.

• Estimated Travel: 20-30%

Physical requirements

May include sitting or standing for extended periods, working with computers and technical equipment, and occasionally lifting or moving materials or tools.

Direct reports

N/A

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.