Applied Scientist II

Apply advanced statistical modeling, machine learning, and analytics techniques to tackle complex problems such as fraud/anomaly detection, opportunities and business impact analytics. Design and analyze experiments to validate hypotheses and measure impact on products. Communicate findings and recommendations to technical and business stakeholders through clear, actionable insights. Drive projects from concept to production in a fast-paced, dynamic environment. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience. 2+ years of experience in Python/R/Scala or similar technology. 2+ years of experience in data science, analytics, or related areas. 1+ years of experience in applied machine learning and statistical modeling. These requirements include but are not limited to the following specialized security screenings: Experience in the ability to structure un-scoped problems, define success metrics, and drive execution under uncertainty. Experience moving applied research into shipped product features Experience with SQL/R/Python/or similar to implement statistical models, machine learning, and analysis in big data environment. Experience in large scale computing systems like Spark, Hadoop, MapReduce and/or similar systems.