Applied Data Scientist, Operational Analytics

This is a role for someone who likes to understand a dataset deeply and to find structure where others see noise. You will work across the raw operational data Atlas uses, identify the signals that matter, and design the analytical approaches that the intelligence layer is built on.

• Analyze operational data across domains to find the signals that precede disruption, shortage, or failure.
• Design the analytical approaches and metrics that the intelligence layer uses to reason about operational state.
• Work with ML engineers and research scientists to translate analytical findings into models.
• Produce written analyses that the wider team can read and act on.
• Help the company and its clients understand what the data actually says, including when it says less than we want.

• Strong applied statistics and analytical skills, with a bias toward finding real answers rather than elegant ones.
• Comfort with large, messy, operational datasets.
• Strong SQL and Python.
• Ability to communicate findings clearly to engineers, domain experts, and non-technical stakeholders.

These are not required. They are the kind of background that tends to do well in this role.

• Experience in operations, logistics, energy, or public-sector analytics.
• Background in industrial or engineering systems.