Data Analyst - Predictive Analytics
California, United States
• Modeled various logistical, financial, and strategic requirements utilizing Microsoft SQL Server, Python 3.x, and Microsoft Excel. Developed for wide audiences from operations to C-suite.• Lead prototype development of corporate reporting, including new data marts, utilizing industry leading data lake and data cube technology.• United various departments in ad-hoc requests and break-fix items to bring a speedy and reliable resolution to the identified issues. • Optimized shipping logistics by transitioning 40% of marketing order deliveries from 2-day air shipping to standard ground, saving approximately $30 per device. This adjustment resulted in annual savings of $840,000, considering the volume of 70,000 marketing orders per year.• Performed QA throughout various integrated data systems, including Salesforce, to ensure data validation/cleaning was robust. Outline methods to optimize data solutions which further prevent data integrity leaks.• Designed and implemented a Call-Based Routing strategy, leveraging predictive analytics to establish a 95% confidence level for deploying an Automatic Speech Recognition (ASR) model. This strategic shift saved the company over $100M in EBITDA by significantly reducing reliance on costlier live-agent interventions.• Defined various corporate KPI measures to provide standardization in calculation and data sources throughout corporate level reporting. • Collaborated with many business owners to ensure all business logic operates as expected with related reporting aligning to existing business rules.• Revolutionized the inside sales strategy by analyzing call data to reveal that 95% of sales were achieved within the first 8 calls. By cutting call efforts by 55% without affecting conversion rates, achieved a cost saving of roughly $2.5 million in annual headcount expenses.• Developed statistical modeling on customer behavior to determine optimal outreach programs to drive customer retention and adoption.