Mid-Level Python Data Scientist [$318k/yr+] TS/SCI-FS Poly with Security Clearance
Quick Overview
Job Description
Candidates must already possess an active Top Secret/SCI w/ Full Scope Polygraph to be considered.
Summary: • Build and develop artificial intelligence models, machine learning algorithms, and statistical solutions. • Translate complex data analysis into automated analytics and intuitive data visualizations. • Utilize software development expertise in Python, R, or MATLAB to solve challenging analytical problems.
Qualifications && Compensation: • Degree: Technical bachelor's degree or equivalent experience • Years of experience: 10+ years • Total Compensation: $318k+ yearly Job Description: • Build, test, and refine AI and machine learning models for operational reliability and relevance. • Analyze algorithms and protocols while fine-tuning input and model parameters. • Develop data mining, statistical, and graph-based algorithms to analyze and interpret complex datasets. • Prototype alternative algorithms and evaluate performance metrics to select optimal production models. • Design experiments and models to generate synthetic data when training datasets are unavailable. • Create reports and visualizations summarizing data trends and delivering actionable insights. • Partner with subject matter experts to convert manual analysis processes into automated analytics. • Implement prototype algorithms within production frameworks to integrate seamlessly into analyst workflows.
About SYSTOLIC: SYSTOLIC is dedicated to giving our employees the best possible company experience so that they can focus on providing outstanding support to their customer’s mission. Our company is founded on integrity, enthusiasm, and a relentless commitment to supporting the Intelligence Community. You can learn more about us and submit an application to be considered against our current and future openings at https://systolic.com. To learn about our compensation ranges, visit our
Pay Transparency page at: https://systolic.com/pay-transparency
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