Data Scientist 3

Develop machine learning, data mining, statistical, and graph-based algorithms to analyze datasets. Prototype and select optimal algorithms based on performance metrics. Build models or develop experiments to generate data when training datasets are unavailable. Generate reports and visualizations summarizing data and providing insights. Partner with subject matter experts to automate manual data analysis. Implement prototype algorithms within production frameworks for analyst workflows. Produce data visualizations, extract information from various data formats, and incorporate SME input into feature vectors. Translate customer analysis processes into quantitative formulations for software prototypes. Develop and implement statistical, machine learning, and heuristic techniques for descriptive, predictive, and prescriptive analytics. Develop statistical tests for data-driven recommendations and decisions. Develop experiments to collect data or simulate data when needed. Develop feature vectors for machine learning algorithms. Identify and tune the most appropriate algorithms for datasets. Evaluate and validate analytic performance using standard techniques and metrics. Oversee the development of analytic efforts, guide teams in analytic development, and ensure scalability to large datasets. Partner with software engineers and cloud developers for production analytics. Develop and train machine learning systems for mission automation. Lead teams in developing multiple analytic efforts. Define analytic requirements with customers and SMEs. Guide the transition of prototyped analytics to production systems. Understand and integrate emerging machine learning and pattern recognition algorithms. Delegate analysis responsibilities and monitor team performance.