Senior Data Scientist in Springfield

Energy Jobline
Springfield, MO, United States
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$154,050.0 - $278,475.0
Working hours
Regular working hours

Tech stack

Big Data Python (Programming Language) Information Technology Software Library

Requirements

The Senior Data Scientist will lead complex analytics efforts across the full solution lifecycle-from problem definition and requirements development through design, implementation, deployment, and ongoing operations and maintenance (O&M). The ideal candidate brings deep technical expertise, strong mission awareness, and the ability to communicate analytic insights to senior decision-makers., Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field with 15+ years of relevant experience, or Bachelor’s degree with 18+ years of relevant experience \n

  • \n Extensive experience applying data science and advanced analytics to complex, mission-focused problems \n

  • \n Expert-level proficiency in Python and/or R, including advanced data science and machine learning libraries \n

  • \n Strong experience working with large, complex datasets from multiple sources \n

  • \n Demonstrated ability to lead technical efforts and influence analytic direction on large or complex programs, Strong written and verbal communication skills, including briefing senior leaders

Benefits & conditions

n \n

  • \n Serve as a senior technical contributor and analytic lead on complex, high-impact security programs \n

  • \n Partner with government customers and subject matter experts to define mission problems and analytic objectives \n

  • \n Translate ambiguous operational challenges into actionable data science requirements and solution designs \n

  • \n Design, develop, and deploy advanced analytics, statistical models, and machine learning solutions \n

  • \n Apply advanced data science techniques including exploratory data analysis, feature engineering, predictive modeling, hypothesis testing, and algorithm development \n

  • \n Integrate structured and unstructured data from diverse sources across classified environments \n

  • \n Communicate analytic findings, insights, and recommendations to senior technical and non-technical stakeholders \n

  • \n Support deployment, monitoring, and ongoing operations and maintenance (O&M) of analytic solutions \n

  • \n Mentor and guide junior data scientists and contribute to analytic standards, best practices, and reusable frameworks \n

  • \n Maintain awareness of emerging data science, AI, and big-data technologies relevant to security missions \n

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Apply for this position

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