Software Engineer - Forecasting & Scheduling

Assembled • $120K — $150K *
San Francisco, CA 94112In-Person
Information Technology
Less than 5 years of experience
4 weeks ago
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in machine learning or algorithm development.
  • Familiarity with Python libraries such as pandas, SciPy, and seaborn.
  • Proven background working in machine learning or algorithmic teams.
  • Strong commitment to improving statistical and runtime performance.
  • Ability to analyze and implement complex scheduling algorithms.

Responsibilities

  • Develop forecasting interfaces to predict support contact volume.
  • Design data pipelines for optimal agent scheduling.
  • Implement interfaces that accommodate agent preferences and labor constraints.
  • Enhance machine learning operations for rapid model deployment.
  • Iterate on predictive models to improve accuracy and efficiency.

Benefits

  • Inclusive workplace culture that values diverse perspectives.
  • Opportunity to work on innovative data-driven projects.
  • Encouragement for candidates with unconventional career paths or backgrounds to apply.
Full Job Description
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. (check out https://en.wikipedia.org/wiki/Nurse_scheduling_problem)
  • 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.


We know great candidates don't always meet every requirement listed in a job description. If the role excites you and you believe you can make an impact at Assembled, we encourage you to apply. We value diverse perspectives and are committed to building an inclusive workplace where everyone feels like they belong and has the opportunity to do their best work. We look forward to hearing from you!

About Assembled

Assembled is a workforce management software company founded in 2018 by Ryan Denehy and is headquartered in San Francisco, California. Assembled provides a platform for customer support teams to manage their workforce, including scheduling, forecasting, and performance tracking. The software includes features such as real-time analytics, automated scheduling, and integrations with other customer support tools. Assembled is used by companies such as Stripe, Harry's, and GoFundMe.
Learn more about Assembled
Size
50 employees
Industry
Enterprise Technology
* Ladders Estimates

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