• Evolve the Interactive Learning Plugin's recommendation system • Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations. • Build and operate applied models • Develop, validate, version, monitor, and iterate on models used by the recommendation system. • Define what recommendation quality means • Develop offline, online, and longitudinal measures of recommendation performance. • Ship incremental improvements • Use the data and infrastructure available today while identifying the instrumentation and platform capabilities needed tomorrow. • Partner across disciplines • Work closely with software engineers & data analysts to productionize models and integrate them safely into the recommender service. • Partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis.

• Evolve the Interactive Learning Plugin's recommendation system • Build and operate applied models • Define what recommendation quality means • Ship incremental improvements • Partner across disciplines

• Evolve the Interactive Learning Plugin's recommendation system • Build and operate applied models for recommendation system • Define what recommendation quality means and develop measures • Ship incremental improvements and integrate them into the existing recommender • Partner with software engineers and data analysts to productionize models

• Evolve the Interactive Learning Plugin's recommendation system. • Build and operate applied models. • Define what recommendation quality means. • Ship incremental improvements. • Partner across disciplines.