Software Engineer - Forecasting & Scheduling
Develops forecasting interfaces, data pipelines, and scheduling systems to predict support contact volume and optimize agent schedules for thousands, incorporating ML models and constraints like labor laws. Requires Python/ML experience and performance focus.
About the job
What you’ll work on
- Predicting contact volume: Developing forecasting interfaces, data pipelines, and inference servers to predict support contact volume and determine the optimal number of support agents required for specific days and times.
- Scheduling 1000s of support agents: Designing and implementing interfaces to collect and store team preferences and customer business constraints (e.g., labor laws), enabling the creation of optimal schedules for teams of thousands of support agents based on these forecasts and constraints.
- MLOps: Enhancing machine learning efficiency and operations to support rapid model deployment and iteration.
About you (specifically)
- Familiarity with ML packages and software: Experience using Python libraries like pandas, SciPy, and seaborn for statistical or predictive work.
- Background in ML or algorithmic teams: Previous experience working on a machine learning or algorithmic team.
- Passion for performance: A strong commitment to advancing both statistical and runtime performance, ensuring reliable and efficient forecasting and scheduling.
Skills
Python, pandas, Scipy, Seaborn, Machine Learning, MLOps, Data Pipelines, Forecasting, Scheduling Algorithms, Inference Servers
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