Lead Assistant Manager

Job Description: Data Scientist - Forecasting We are seeking a highly analytical and experienced Data Scientist to join our Workforce Planning or Analytics team. The ideal candidate will focus on long-term forecasting for contact center operations, leveraging machine learning models and advanced analytics to drive data-informed decisions using Python, SQL and Power BI. You will play a critical role in projecting future contact volumes, resource requirements, and operational trends, directly supporting strategic planning and optimization efforts across the business. Key Responsibilities Analytics & Insights: Analyze historical trends and seasonality to make informed decisions. Apply machine learning and statistical techniques (e.g., ARIMA, Prophet, XGBoost, LSTM, etc.) to improve forecast accuracy over months and years. Conduct in-depth analysis using Excel or Python to identify key drivers of change in volume. Generate Forecast: Generate monthly forecasts for multiple lobs using machine learning models. Monitor and adjust forecasts based on trends, seasonality, and business updates. Forecast assessment: Evaluate forecast accuracy every month and present key findings. Monitor forecast performance, diagnose deviations, and continuously improve model performance using feedback loops and model validation. Stakeholder Collaboration: Present analytical findings and strategic recommendations to stakeholders, especially around critical days or events. Collaborate with cross-functional teams to understand business requirements and deliver analytical solutions Required Skills & Expertise Technical Skills: Proficiency in Excel, SQL and Python for advanced data analysis, data extraction and data manipulation Hands-on experience with data visualization tools (e.g., Tableau, Power BI) is a plus. Analytical Acumen: Advanced knowledge of Time Series forecasting techniques or Contact Center demand volume forecasting. Ability to work with large datasets and extract meaningful insights to generate forecasts Ability to work on ad-hoc requests to support business needs and derive actionable insights Problem-Solving & Communication: Strong problem-solving skills, with the ability to translate complex analytical findings into clear and actionable recommendations. Excellent communication and data storytelling skills; able to influence stakeholders using evidence-based insights Candidate Profile Educational Background: Bachelor’s/Master’s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field. Professional Experience: At least 3-5 years of experience in the data analytics with good experience of Time Series Forecasting. Show more Show less