Master's degree in Data Science, Statistics, Applied Mathematics, or related field; undergraduate in Engineering, Mathematics, Economics, or Computer Science.
Proficient in Python and SQL; experienced with large, complex datasets.
Background in machine learning and optimization models with a strong statistical intuition.
Familiarity with data pipelines to engage effectively with data engineers.
Strong analytical skills combined with practical common sense.
Building-oriented mindset for breaking down problems and enhancing solutions.
Ability to navigate ambiguity and prioritize asking insightful questions.
Experience in supply chain and logistics is preferred; knowledge of complex systems is valuable.
Responsibilities
Understand the operational workflows and decision-making processes of customer businesses.
Interpret customer data to identify meaning and contextual relationships.
Formulate and test hypotheses to validate data-driven insights.
Develop inference techniques and regression models to analyze relationships.
Translate business goals into mathematical constraints and calculations.
Identify gaps in processes and data to improve operational efficiency.
Act as the bridge between applied science and data engineering, translating requirements accurately.
Benefits
Comprehensive medical, dental, and vision insurance.
401(k) plan with company matching contributions.
Commuter benefits to assist with transportation costs.
Investments in employee health and financial future.
Full Job Description
What You'll Do
Understand how customer businesses actually operate: how work flows, where decisions are made, and what good looks like operationally.
Interpret customer data and assign context - figure out what the data means, how entities relate, and where the gaps and inconsistencies are.
Form and test hypotheses using data to prove or disprove ideas about the system and the relationships between entities within it.
Build inference techniques and regression models that extract signal and quantify relationships.
Translate business logic and objectives into mathematical constraints and quantifiable calculations.
Identify missing concepts needed to close process and data loops - spot what isn't there yet but needs to be.
Serve as the critical link between applied science and data engineering: translate scientific requirements into engineering specifications and vice versa.
What You Bring
Master's degree in Data Science, Statistics, Applied Mathematics, or a related quantitative field; undergraduate degree in Engineering, Mathematics, Economics, or Computer Science.
Strong proficiency in Python and SQL; comfortable working with large, messy, real-world datasets.
Experience with machine learning and optimization models, with strong statistical intuition - you notice when results look wrong and can articulate why.
Enough familiarity with data pipelines and infrastructure to have productive technical conversations with data engineers.
Sharp analytical instincts paired with strong common sense: you can tell when something doesn't add up, and you use data to prove or disprove it.
A builder's mindset - you break problems into testable components, take things apart, and improve them.
Comfort with ambiguity and a bias toward asking the right question before assuming the right answer.
Supply chain and logistics experience is ideal. Hands-on experience with any complex, interrelated physical system is highly beneficial. Candidates who demonstrate the smarts, drive, and curiosity described above are encouraged to apply - we hire for potential.
Compensation & Benefits
As part of our commitment to People Powered Greatness, we invest in our team members with competitive compensation and a comprehensive benefits to support your health, financial future, and daily life. The package includes medical, dental, and vision coverage, a 401(k) with company match, and commuter benefits. Total compensation may include a combination of a competitive base salary and equity. Your initial placement within our salary range will be based on your experience, qualifications.
The base pay range for this role is $180,000 - $250,000 per year.
