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Keystone AI

Enterprise AI for forecasting and optimization

MBA Consultant

Strategy & Management ConsultingConfirmed live in the last 24 hours
Full-time$140k - $198k /yr

About the Job

Requirements

  • An MBA is required.
  • A bachelor's degree in Economics, Econometrics, Finance, Mathematics, or a closely related field from a top university is required; target GPA is 3.7 or higher.
  • At least five years of relevant experience in consulting, product management, data science, or strategy-oriented roles.
  • Demonstrated experience owning discrete projects or workstreams, rather than only contributing to them.
  • Exposure to strategy consulting, economic consulting, investment banking, private equity, or data- and technology-driven environments.
  • Evidence of academic or leadership excellence, such as honors, Dean’s List, or leadership roles.
  • Strong quantitative and problem-solving skills, with the ability to independently structure analytical approaches.
  • Proficiency in Python, R, or Stata, with experience working with large, complex datasets.
  • Ability to translate ambiguous questions into structured analyses and actionable insights.
  • Solid business and economic intuition.
  • Clear, structured communication, with the ability to connect analysis to business and economic implications.
  • Comfort operating in ambiguity and driving workstreams forward with limited guidance.
  • Experience mentoring or guiding junior team members and reviewing work for quality.
  • Strong ownership mindset, bias toward action, and accountability for outcomes.
  • Clear interest in litigation consulting and Keystone’s problem space.

Responsibilities

  • Own and structure end-to-end analytical workstreams, translating ambiguous business or economic questions into rigorous, testable analytical approaches.
  • Design and implement advanced quantitative and econometric analyses, such as regression, causal inference, forecasting, or simulation models, using Python, R, or Stata.
  • Independently assess data quality, define methodologies, and select appropriate modeling approaches, making trade-offs under uncertainty.
  • Interpret results in a business or economic context, drawing out implications, risks, and limitations rather than merely reporting outputs.
  • Guide and review Associate-level work, ensuring analytical rigor, efficiency, and quality of execution.
  • Lead targeted research efforts to inform problem framing, hypothesis development, and analytical design.
  • Synthesize economic theory, industry dynamics, and technical constraints into structured hypotheses and analytical plans.
  • Critically evaluate academic, regulatory, and market-data sources and determine what materially impacts the case or client decision.
  • Connect qualitative insights with quantitative findings to refine direction and challenge initial assumptions.
  • Drive development of clear, structured narratives that link analysis to actionable insights and recommendations.
  • Translate complex analytical outputs into persuasive, client-ready materials tailored to technical and non-technical stakeholders.
  • Own significant sections of client deliverables, including reports, memos, and presentations, ensuring clarity, logical flow, and defensibility.
  • Communicate findings and implications in internal and client discussions, contributing to decision-making and shaping team direction.
  • Develop high-impact exhibits that convey analytical rigor and strategic insight.

Desired Qualifications

  • A Master's degree in Analytics, Data Science, Economics, or a related field is a plus.

About the Company

Keystone AI

Enterprise AI for forecasting and optimization

Keystone.AI commercializes the DEEP Enterprise AI platform that places neural-network-based prediction and decision systems at the core of large enterprises' operating models to optimize supply chains and free cash flow. It works by transforming ERP data (orders, shipments, invoices) into fine-grained event streams using its RAIN encoding, then the DEEP platform uses these streams with its Foundation Forecasting model to predict demand and optimize production, inventory, fulfillment, and capacity planning. It differentiates itself by embedding DEEP inside clients' existing cloud environments (AWS/Azure/GCP) and ERP/planning ecosystems (SAP, Oracle, Kinaxis, o9, OMP) and by acting as a scientific predictor and decision engine built on Keystone's methodological lineage. Its goal is to become the enterprise's central science-based predictor and decision tool that reduces forecast errors, improves operational efficiency, and enhances free cash flow for global supply chains.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Bellevue, WA
Founded
2003

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