SalaryUSD TBD TBD
- Anomaly Detection and Analysis : Responsible for anomaly detection across operational metrics, isolating such anomalies to root cause, and recommending optimizations across process, policy, and platforms to reduce transactional costs while improving the customer experience.
- Reactive Anomaly: Identify anomalies across the Customer Care domain including (but not limited to) transactions relating to Account Services, Technical Support, Professional Installation, Self-Installation, Customer Onboarding, and specific Products and Devices.
- Proactive Anomaly: Analyze the transaction funnel to identify optimization opportunities across process, policy, and platforms. This function will serve to 'seed new opportunities across the ACOE, driving discovery and analysis through the ACOEs Structured Innovation process.
- Root Case Analysis: Deep-dive anomalies to root cause, providing actionable insights and recommendations on remediation strategies, or shaping tight problem statement to hand off to other ACOE teams.
- Care Transaction Reduction : Opportunity identification and root cause isolation across Customer Care process and platform effectiveness.
- Cross Channel Effectiveness : Establish measurement systems to monitor effectiveness across Care-related channels including Solutions Center (technical trouble shooting), Digital Assist, and Cox.com.
- Controlled Experimentation : Design, manage, and measure controlled experiments across Care platforms and processes. Controlled experiments will be 'seeded from anomaly detection and cross channel effectiveness-related analysis.
- End-to-End Measurement System: Build, test, and maintain an end-to-end measurement system that serves as the basis for anomaly detection including data engineering, anomaly model development, and visualization.
- Prepare documentation, reports, and presentations that explain outcome of analytic workstreams.
- Liaise with key stakeholders across Cox Communications to ensure appropriate delivery of analytics.
- Graduate degree in Mathematics, Statistics, Economics, Engineering, Operations Research, or Computer Science
- 5+ years of experience in analytics role in ML, AI, NLP, research, predictive analytics, business analytics or similar area
- Strong programming skills and ability to utilize a variety of data/analytic software/languages/tools; e.g., Spark (ML, Mllib, Spark SQL), R (caret, ggplot2), Python (pandas, numpy, scipy, scikit-learn), Scala, Java, C, Hive, SQL, SAS, Tableau, etc
- Strong communication skills. The ability to successfully comprehend and communicate advanced analytics artifacts, business insights, and resulting implications to non-technical business partners
- Deep understanding of data domains, models, and implications for analytics use in at least one industry including telecommunications, cable, finance, media, advertising, or similar
- Graduate degree in Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Operations Research, Analytics, Engineering or closely related field
- Experience with anomaly detection and root cause analysis
- Practical experience applying advanced ML, DP, and AI approaches to mass transaction reduction and customer experience optimization
- Experience in data visualization solutions and data visualization tools
Data Analytics Engineer, Consultant
Data Platform Architect, Principal
Data Architect (Snowflake/Microstrategy/AWS)