The future is already here.
It's just not evenly distributed yet.

Assembled is seeking an Algorithmic Scientist to join our Planning and Staffing team. In this role, you will drive the core design, development, and implementation of Assembled’s modeling and algorithmic products. These products support the largest customer support teams in the world by predicting their customers’ support needs and the time taken to resolve each case, producing accurate staffing requirements. You will also model how teams can over-staff themselves to achieve inbox zero and generate efficient schedules for when they need to be on the phone compared to answering emails or chats.

This position requires a blend of theoretical expertise and practical application to real-world problems. As the second scientist on the team, you will play a crucial role in shaping the product direction and making key technical decisions within our organization.

What you’ll work on

Some example projects include:

• Algorithmic schedule generation: Build schedules for customer support agents based on requirements from managers and preferences from their team members. We need to take into account break and lunch times, individual preferences, labor laws, and staffing relative to predicted ticket volume.
• Queueing theory for staffing requirements: Most call centers use the primitive M/M/c queue (Erlang-C) to generate staffing requirements for phone lines. However, customers expect to be able to contact support teams through email, chat, or social media. Each of these methods (or channels) breaks the assumptions of the primitive model, as they are asynchronous, concurrent (e.g., agents often handle multiple tickets or chats), or omni-channel (e.g., agents can move between phone and email within the same shift). By joining us in Planning & Staffing, you will work on implementing algorithms that solve our customers’ planning needs and push the industry forward.
• Time series forecasting: We generate forecasts of chat, email, and call volume. Implement state-of-the-art algorithms to optimize short-term accuracy, as well as long-range methods that take into account business variables to inform full-year hiring plans.

About you

• 8 years of experience in a technical role at a high-growth company.
• Have implemented and engrained a scientific approach in a small technology organization previously.
• Experience with production machine learning systems, including activities like data cleaning, experimental design, and model deployment.
• Deep understanding of operations research, optimization, applied statistics, and time-series forecasting.
• Experience writing and maintaining models and pipelines in production.
• Customer focus, with interest in and ability to work directly with users.
• Excited to wear multiple hats, including coding, user interaction, planning, brainstorming, interviewing, and cross-functional collaboration.

Nice to have

• Experience leading a machine learning or algorithm-focused team’s roadmap and architecture.
• Degree in Operations Research, Industrial Engineering, or related field.

The estimated base salary range for this role is $180,000 - $220,000 per year. The base pay offered may vary depending on location, job-related knowledge, skills, and experience. Stock options are provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered.