Responsibilities
- Own the Solutions client experience from discovery to delivery
- The ask, define success criteria, and translate investment theses into concrete deliverables and timelines
- Set expectations early and clearly (scope, feasibility, methodology, tradeoffs), and ensure deadlines are hit
- Lead discovery with prospects and clients to uncover the “real question” behind
- Partner with Revenue to drive Solutions growth (commercial + scoping)
- Support client conversations by articulating Solutions’ value: technical execution + on-demand library access + proprietary infrastructure
- Help package and scope engagements across commercial models (ad hoc credit-based work vs. dedicated “full partnership” resourcing)
- Lead a high-performing delivery team
- Manage, mentor, and develop a team of data/insights analysts executing incoming and recurring projects
- Establish quality bars for analytical rigor, reproducibility, and “client-ready” outputs (clean narratives + clear assumptions + defensible methods)
- Deliver bespoke outputs across the full YipitData library
- Leverage (and help clients navigate) a broad set of dataset types—e.g., email receipt panels, transaction data, software spend, web traffic, app data, web-scraped data, connected accounts, healthcare purchasing, and targeted interviews
- Drive delivery across one-off deep dives and ongoing feeds (examples include market share files, targeted interviews, custom scrapers, and recurring deliveries built to client specifications)
- Build the “operating system” for Solutions
- Define best practices for intake, scoping, project management, QA, and reuse (templates, playbooks, repeatable pipelines)
- Improve capacity planning, prioritization, and visibility across the Solutions pipeline
- Leverage AI to scale Solutions delivery and increase capacity
- Identify and implement AI-enabled workflows (e.g., assisted scoping, faster data QA, automated recurring deliverables, narrative drafting) to improve turnaround times, consistency, and team throughput while maintaining a high quality bar
- Build reusable, AI-assisted “solution kits” and automation for repeatable work
- Develop templates, playbooks, and lightweight automation (prompt libraries, reusable code modules, standardized pipelines) that reduce manual effort across common Solutions requests and enable the team to deliver more projects per analyst without sacrificing rigor or client readiness
Requirements
- 5+ years of experience using alternative data to answer high-impact questions, plus 1–2 years of people leadership (or clear examples of leading teams/projects).
- Have worked directly with end clients and can consistently uncover the underlying need behind the request.
- Have experience with, and a strong interest in, leveraging AI to enhance ETL, data pipelines, and analytical workflows.
- Are comfortable with SQL and Python, and have experience building/maintaining production-grade workflows (Databricks/Spark/GitHub familiarity a plus).
- Have strong experience working with large, messy, evolving datasets—especially where definitions/taxonomies change.
- Bring strong commercial instincts: you can partner with Revenue to scope work cleanly and deliver an excellent, repeatable client experience.
Nice to Have
- exposure to institutional investor workflows and stakeholders (fundamental analysts and/or data teams)
