Wargaming & Modeling Analyst

Assertive Professionals is seeking a Wargaming & Modeling Analyst supporting our National Security Customer in Charlottesville, VA. This is an open and funded position. We are offering a salary of $150,000 with a $2,000 sign-on bonus or reimbursable relocation . This is a great opportunity to work for an employee-centric, fast-growing small business. We offer an excellent benefits package, including PTO (accrual rates vary by contract and customer requirements), 401(k) Match at 5%, Profit Sharing, Company-paid Life Insurance, Dental, Vision, STD/LTD, and two options under a national medical plan with employee contribution. This position currently provides 3.33 hours of Paid Time Off (PTO) per pay period and 88 hours of federal holidays. There is an additional $1,200 annual corporate bonus for time and attendance compliance! Responsibilities Include: Conducting data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis, and uses scientific techniques to correlate data into graphical, written, visual and verbal narrative products, enabling more informed analytic decisions. Proactively retrieves information from various sources, analyzes it for better understanding about the data set, and builds AI tools that automate certain processes. Duties typically include creating various ML-based tools or processes, such as recommendation engines or automated lead scoring systems, as well as supporting wargaming and modeling & simulation (M&S) events through scenario design, data ingest and preparation, game piece and map development, and adjudication support. Performs statistical analysis, applies data mining techniques, and builds high quality prediction systems, including simulation-based models used to inform wargame outcomes and decision-support products. Should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms. Should have prior experience with large data Multi-INT analytics, ML, and automated predictive analytics, as well as experience applying analytic and modeling techniques within a wargaming or exercise support environment. Required Experience and Qualifications: TS/SCI Clearance 12 years relevant experience with Master's Degree, OR 17 years relevant experience with Bachelor's Degree Demonstrated experience developing wargames and force-on-force scenarios for threat nation invasion contingencies, including analysis of battle-type factors such as force ratios, national/armed forces strengths and weaknesses, quality and numbers of weapons and equipment, national and armed forces doctrines, and intangibles such as esprit de corps and morale Demonstrated experience conducting data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis to correlate data into graphical, written, visual, and verbal narrative products Demonstrated experience retrieving information from various sources and building AI tools/processes that automate analytic workflows, including ML-based tools such as recommendation engines or automated scoring systems Demonstrated experience performing statistical analysis, applying data mining techniques, and building prediction systems Demonstrated proficiency in data visualization and graphical applications, including Power BI and Tableau Demonstrated proficiency in major data science languages, including R and Python Demonstrated experience managing and merging disparate data sources, preferably through R, Python, or SQL Demonstrated prior experience with large data Multi-INT analytics, ML, and automated predictive analytics Demonstrated experience collecting, analyzing, and interpreting large-scale data sets to develop data-driven solutions supporting an intelligence division's analytical mission, including ensuring data integrity Demonstrated technical competency in statistics, coding languages, databases, machine learning, reporting technologies, and data standards Demonstrated ability to work independently with minimal to no oversight Demonstrated ability to review analytic products for cogent arguments, tradecraft standards, and adequate support for conclusions