Data Scientist - Law Enforcement Analytics & Program

• Translate business challenges into clear, actionable requirements for AI-enabled solutions
• Map end-to-end business processes, highlighting areas where AI can drive efficiency and value
• Design, build and implement AI automations
• Develop and deploy solutions and AI prompts to identify and address bottlenecks, replacing manual interventions with intelligent automation
• Create scalable automation mechanisms that proactively monitor, analyze, and report
• Build robust predictive models using statistical and machine learning techniques to forecast risks, anticipate issues and optimize
• Develop monitoring tools to trigger early warnings and facilitate rapid resolution through automation
• Acts as a data subject matter
• Formulate the right metrics, measures, and definitions of success to drive quality, efficiency, cost, and timeliness understanding the source data
• Perform complex data analysis leveraging data streams available to drive proactive and predictive action
• Partner with operational analysts , investigators and engineering partner to understand pain points, identify repetitive tasks and translate them into opportunities for automation
• Bring multiple areas of business and engineering together via a common reliable foundation of common data, metrics, and insights
• Build data tables and dashboards, and leverage these for interpreting incidents and trends
• Leverage tools like Tableau, Python, and SQL to drive efficient analytics

• Bachelor's Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, or Data Science)
• 6+ years of experience in analytics, engineering, and use of AI/ML
• 6+ years of SQL development experience and scripting language like Python
• Hands-on experience with AI/ML frameworks (e.g. TensorFlow, PyTorch, Scikit-learn) and automation tools/platforms
• Significant experience with data visualization tools and leveraging data models to drive business decisions
• Experience with statistics (e.g. statistics basics, statistical modeling, experimental design, hypothesis testing, etc.)
• Demonstrated experience with proactively identifying, scoping and implementing solutions
• Hands-on experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across stakeholders

Master's Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, or Data Science)

• bonus
• equity
• benefits