Turn a loosely framed client question into a defined analytical problem, breaking it into components, identifying which ones are load bearing, and framing two or three approaches before the work starts; Expect a first approach to break, treat each failed attempt as information, and return with what was learned and the next variant in hand; Work from limited or imperfect data to build a defensible view of a market, offering, or business model when no clean comparable exists, reasoning from first principles about who pays and what the unit of scale is, triangulating from smart proxies, and sizing markets bottom up; Design financial and operating models from a blank workbook, matching the form of the analysis to the question and building driver based structures that mirror how the business actually works; Isolate and clearly label every assumption so clients and colleagues can follow the logic and pressure-test it, prioritize the variables that actually drive business impact, and avoid getting lost in analysis for analysis’s sake; Pull, clean, join, and segment client data in Python, including unstructured inputs such as free text CRM notes, and sanity check findings against reality before presenting them; Convert analyses that worked into parameterized models, dashboards, or scripted pipelines that clients can run and maintain after the engagement ends; Synthesize learnings into clear and actionable strategic deliverables that lead with the answer and hold up under a hostile read, and present them to executive audiences with internal and client teams, defending the argument without the deck when needed; Collaborate with, and take input from brand, innovation, and experience strategists, engagement managers, designers, and clients from different backgrounds; Arrive at working sessions with a draft of the answer, what you have ruled out, and where you want input, and share work at 60 percent confidence so the team can shape it early; Direct the contributions of Strategists and Associate Strategists on your workstream, review their work for logic and rigor before it reaches the client, and turn what each engagement taught you into methods and assets the team reuses. 4-7 years of client side or consulting experience in corporate strategy, growth strategy, or new venture development, owning the analysis behind growth, business model, or investment decisions and presenting it to executive audiences; Undergraduate and/or graduate degree in economics, finance, engineering, business administration, accounting, or related disciplines preferred; Experience working with large and messy data sets to identify insights and commercial opportunities; An advanced command of Excel and financial modeling, with a track record of building models from scratch that others could audit; Working fluency in Python and comfort with AI assisted building such as Claude Cowork or Claude Code (bonus: a client tool or dashboard you have shipped); Comfortable working with collaboration tools and communication platforms (Slack, Google Suite, AI, Figma, etc.) and willing to experiment with new ones; Comfortable moving forward amidst ambiguity, working with imperfect data sets, and getting functionally conversant in a new industry within days; Based in New York metro area; Willing to travel up to 25% for client meetings.