FAQs
What is the primary responsibility of the Lead Assistant Manager for the Data Analyst/Forecaster role?
The primary responsibility includes developing short-term demand volume forecasts and creating impactful accuracy assessment dashboards to drive data-informed decisions.
What technical skills are required for this position?
Proficiency in Excel, SQL, and Python for advanced data analysis, data extraction, and data manipulation is required. Experience with data visualization tools like Tableau or Power BI is a plus.
How much professional experience is necessary for candidates applying to this role?
Candidates should have at least 2-3 years of experience in data analytics, with a good background in Time Series Forecasting.
What analytical techniques should the candidate be familiar with?
Candidates should have advanced knowledge of Time Series forecasting techniques or Contact Center demand volume forecasting.
Will the Data Analyst/Forecaster have to collaborate with other teams?
Yes, the role involves collaboration with cross-functional teams to understand business requirements and deliver analytical solutions.
Is formal education important for this role?
Yes, a Bachelor’s or Master’s degree in Analytics, Data Science, Economics, Statistics, Engineering, or a related field is required.
How often will the forecast accuracy be evaluated?
Forecast accuracy will be evaluated weekly, and key findings will be presented regarding high variance days.
What type of forecasts will the candidate be generating?
The candidate will be generating weekly forecasts for multiple lines of business using Python models.
What is expected from the candidate in terms of communication skills?
The candidate should possess excellent communication and presentation skills, with experience delivering insights to senior stakeholders.
Will the candidate be involved in ad-hoc requests?
Yes, the candidate will work on ad-hoc requests to support business needs and derive actionable insights.