Justin Oscapinski

Overall Impact - Worked across the C-suite to define strategies and implement Analytical and Machine Learning Products that:

• Generated $350M in operational cost savings related to simplifying the customer experience and decreasing customer effort
• Generated $135M in improved margin through customer retention efforts

Strategy and Metric Development: Development of measurement strategy focused on a customer centric view of reliability, care and repair experiences with the goal of minimizing unnecessary customer effort and increasing the customer's perception of service and reliability.

• Developed 5 new metrics that were used to manage company wide performance through bonus incentives.

Predictive Modeling: Lead teams using machine telemetry data to predict negative customer experience likely to lead to interactions to inform decisions on proactive experiences and understand how to minimize customer effort.

• Built algorithm to infer how important devices were to in-home internet experience based on time of day and day of week usage patterns and total data usage
• Developed framework to assess and prioritize issue resolution proactively based on predictions of a customers likelihood to interact with our care channel based on usage patterns and radio signals - identified customer bases up to 60x more likely to call us in the day compared to baseline
• Used Latency and Packet Retransmittion measures along with data usage to predict when a customer was having a WiFi-Specific issue
• Developed customer segmentation focused on requirements of services based on connected devices within the home and daily usage patterns to create treatments aimed at diminishing risk from Fixed Wireless and Fiber competitors

Data Product Management: Worked in collaboration with architecture, data management, engineering and business partners to design a holistic customer experience data strategy aimed at enabling accessibility to network related data and increasing visibility into service, sales, marketing and finance activities related to the network. Informed prioritization for all data management, quality and engineering activities based on business goals and long range plans.

• Created a multiyear analytical and product roadmap
• Led cross-functional and organizational teams from product ideation through final production

Product and Engineering Analytics and Testing: Designing experiments and developing normalized analyses to generate causal or minimally biased insights to understand product performance in the internet engineering space.

Team Leadership and Development: Manage and develop data scientists and product analysts at Sr IC and Jr Management Levels

• Collaborated with executive leadership on analytical approaches to solving strategic problems within the CX and Technology organizations
• Analyzed electrical signal and customer usage patterns to understand when customers were likely to impacted by network-related issues
• Developed models to understand customer relationship outcomes and operational impact when network related issues occur
• Developed descriptive and predictive analytics to answer strategic questions across Product and CX Organizations
• Mentored junior staff and taught best practices for data engineering and approaches for analytical solutions
• Structured A/B tests to develop causal inference for customer outcomes based on company interventions

• Built a model for the procurement business that automated the classification of credit card spend and supplier identification using textual analysis