Vice President - Quant Analytics Manager - Demand Forecasting

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase’s call centers, back office, and ~5,200 retail branches.

Forecasting is responsible for the short to long term volume demand planning across CCB operations. The role is focused on Demand Planning, Statistical forecasting, data analysis and actively participating in automation of processes. 

As a Vice President - Quant Analytics Manager in the Workforce Planning & Forecasting team, you will apply operational analytics and strategy tools to enhance integrated planning process, identify enhancements to the forecasting process to provide key business insights.

Job responsibilities

• Lead the forecasting vision, strategy and roadmap
• Manage a team of highly-capable and independent sole contributors, along with mentor, coach and grow people earlier in their careers In this role
• Attract, develop and retain forecasting talent to ensure the team continues to enhance its value to the company
• Develop and implement forecasting processes, forecasts and quality standards for various durations of forecasts.
• Ensure high-quality and accurate forecasts through best practices and continuous improvement.
• Oversee consultative partnerships across multiple stakeholders with strong understanding of business drivers and underlying data 
• Lead and persuade others while positively influencing the outcome of team efforts

Required qualifications, capabilities, and skills

• Master’s Degree with 8+ years or Doctorate (PhD) with 6+ years of experience operating as an analytics professional in a quantitative field: Statistics, Analytics, Data Science, Economics, Mathematics, Business, and related disciplines 
• 5+ years of direct people leadership experience.
• Hands-on experience developing short-term, medium-term and long-term forecasts and experience with time series methodologies
• Deep understanding of theory behind forecast algorithms and methodologies
• Proficient in analytics tools or programming languages like Python, R or SAS & familiarity with basic data table operations (SQL, Hive, etc.)
• Strong analytical thinking, influence and problem-solving
• Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence

Preferred qualifications, capabilities, and skills

• Advanced expertise with Time Series forecasting techniques
• Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. 
• Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
• Previous experience leading highly complex cross-functional projects with multiple stakeholders.