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Mariana Minerals
San Francisco, California, US; Houston, Texas, US; Ann Arbor, Michigan, United States
Source: Mariana Minerals careers · View original posting
From Mariana Minerals's posting. “We” and “our” refer to the employer.
Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We’re reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
Mariana Minerals is a software-first, vertically integrated minerals company supplying the minerals critical to modern energy, AI, and defense technologies. Our data doesn't live in a vacuum — it comes off sensors, assays, lab benches, and plant logs, and it's what the business uses to decide what to run, what to buy, what to fix, and what to build next.
We're hiring a Senior Data Scientist to be the person who makes those numbers trustworthy and legible. You'll own the statistics: how we measure recovery and throughput, how we know a process change actually worked, how much of a swing is signal and how much is assay noise, and what the reporting layer says when an operator or an executive opens it.
This is not an ML modeling role and not a data engineering role. Our MLEs build the models and our data engineers move the data. You bring statistical rigor and clear reporting to a company generating more data than it currently knows how to interpret, and you make sure the conclusions people draw from it are the right ones.
You know the difference between the analysis worth another week and the one that's good enough to decide on today, and you say which is which.
You ask how the data was collected before you analyze it, and you're the person who notices the sensor was miscalibrated for three weeks.
Turn a vague business question into a well-posed statistical one, get the data you need, and own the answer end to end.
Communicate uncertainty in a way that helps people decide, rather than hedging so heavily the analysis becomes useless.
Understand where your data comes from, what the models and simulators downstream do with it, and where the reporting layer sits relative to the platform underneath it.
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