Quant Analytics Associate - Time Series Forecasting Strategist - Workforce Planning

Join the dynamic Workforce Planning organization, highlighting the chance to deliver quantitatively driven solutions and contribute to a team that supports various functions. The Workforce Planning (WFP) organization it is a part of Consumer and Community (CCB) Operations division. The Workforce Planning (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). As a Time Series Demand Forecasting Associate in Workforce Planning, you will be responsible for forecasting contact center demand at the daily and monthly time interval out to several years to assist with resource planning across CCB operations. The role is focused on time-series forecasting, inferential statistics, data analysis and consulting with stakeholders to understand and explain our dynamic business. The role applies operational analytics and strategy tools to enhance the integrated planning process, identify enhancements to the overall the forecasting process while supporting the development of analytical tools. The goal is to provide business insights needed in ensuring that forecasts are appropriately planned and in line with expectations so that our contact center network is optimally staffed, service goals are being met, and budgets are appropriately planned. Job responsibilities: Identify opportunities to enhance existing call volume and productivity forecasting process. Monitor, Evaluate, and Improve Forecast Accuracy: Regularly assess the accuracy of forecasts by comparing them with actual outcomes, implement improvements based on findings, and use common sense approaches to explain changes and reasons for error. Possess strong interpersonal skills for partnering with various levels of the organization and influencing results. Provide analytical leadership to cross-functional team structure that prepares detailed integrated forecasts across multiple lines of business, and segments. Take complex results and communicating them in an easily understood way, focusing on how specific results fit into the bigger picture. Explore opportunities for creating frameworks for automation using Python. Stay Informed on Industry Trends: Keep abreast of industry trends, emerging technologies, and best practices in forecasting to ensure the organization remains competitive and innovative in its approach. Required qualifications, capabilities and skills: Applied knowledge of 3+ years’ experience in business planning and processes: significant forecasting experience, and strong modeling background required. Strong analytical, interpretive, and problem-solving skills with the ability to interpret large amounts of data. Educational Background: MS/PHD Degree in quantitative discipline such as Statistics, Economics, Applied Math, Computer Science, Data Science or Engineering Hands on experience delivering descriptive statistics, inference, and visualizations to communicate with partners and stakeholders. Quantitative Mindset: Strong operational analytic/strategy mindset to identify opportunities and solve them through data and business insights using advanced mathematical approaches. Strong analytical, interpretive, and problem-solving skills with the ability to interpret large amounts of data and its impact in both operational and financial areas. Data Analytics and Software Proficiency: Experience leveraging analytical and statistical tools such as time series, regression, and other forecasting techniques using Python, R, or SAS. Communication skills: Superior written and oral presentation / communication skills – the ability to convey complex information simply and clearly to senior leadership. Demonstrated understanding of business value drivers and aligning teams to achieve business objectives. Hands-on experience and theoretical understanding of time-series forecasting & advanced statistics like Moving Average, Exponential Smoothing, Auto-Regression and Regression. Preferred qualifications, capabilities and skills: Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.). Strong applied technical skills in Python are preferred, with a willingness to transition from SAS or R if necessary. Experience with Spark, Trifacta, HiveQL, Alteryx, and SAS Experience in conducting both exploratory and explanatory analyses, with the ability to deliver clear and effective presentations to stakeholders. Advanced knowledge of Call Center Operations, Contact Center Metrics, and Workforce Planning practices.