Data/ Business Intelligence Sr. Analyst

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Role Summary

GTM analytics, investment-style diligence, and operational intelligence

You will interpret messy datasets, uncover patterns, and convert insights into clear, actionable recommendations that shape how Emergence sources deals, qualifies companies, and supports portfolio success.

This role goes beyond reporting. You will help define how Emergence’s data should be structured end-to-end — across GTM systems, diligence workflows, and portfolio monitoring — and guide engineers on field definitions, transformations, and data models that enable accurate decision-making.

Key Responsibilities

GTM & Pipeline Intelligence

• Analyze funnel health, scoring accuracy, enrichment gaps, stalled deals, and sequencing performance.
• Identify misroutes, inefficiencies, and high-value leads handled incorrectly.
• Build dashboards for sourcing efficiency, outreach performance, and pipeline movement.

Company Diligence & Investment Insights

• Evaluate companies using ARR trends, unit economics, growth signals, product/GTM indicators, and market data.
• Surface early red flags and high-potential opportunities.
• Support pre-diligence with financial, operational, and competitive analysis.

Portco Performance Monitoring

• Track KPIs across revenue, GTM, hiring, product, and operations.
• Flag early risk signals (e.g., pipeline slowdown, churn risk, quota shortfalls).
• Provide monthly summaries for leadership on performance and areas for improvement.

Data Quality & Systems Support

• Maintain clean, consistent datasets across CRM, enrichment tools, and internal systems.
• Support the Architect + Analytics Engineer in validating fields used for scoring, ICP logic, and dashboards.

Dashboarding & Insight Generation

• Build clear, actionable dashboards and proactively surface insights and recommendations that influence GTM strategy, deal prioritization, and portfolio actions.
• Prepare concise, leadership-ready reports that translate data into decisive next steps.

Data Foundations & Modeling

• Define ideal field structures, transformations, and validation rules
• Guide engineering on how to organize and model data to support accurate scoring, ICP classification, GTM workflows, and reporting.
• Define canonical entities, states, and metrics across GTM, diligence, and portfolio systems.
• Partner with engineers to shape tables, joins, transformations, and validation rules that support scoring, funnel logic, and dashboards.
• Ensure metric definitions (e.g., ARR, funnel stages, performance flags) are consistent, explainable, and decision-ready.

Requirements

Core Skills

• Strong SQL + comfort with complex, messy datasets.
• Experience building dashboards (Metabase, Looker, PowerBI, Tableau).
• Ability to synthesize data into actionable insights and strategic recommendations.
• Understanding of SaaS metrics, GTM funnels, and financial indicators.
• Strong ability to frame ambiguous business questions into structured analytical problems and decision-oriented outputs.

Preferred

• Exposure to private equity, venture, consulting, GTM analytics, or portfolio monitoring.
• Experience analyzing company financials or unit economics.
• Familiarity with Python for analysis.
• Ability to work remotely and collaborate effectively with distributed, cross-functional teams.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Statistics, Economics, Finance, Data Analytics, or a related quantitative field (or equivalent practical experience).
• 3-7 years of relevant professional experience in data analysis, business analytics, investment analytics, or operational analytics roles.
• Experience working with complex, multi-source datasets across CRM, financial systems, enrichment tools, or operational platforms.
• Experience operating in fast-paced, evolving environments such as startups, growth-stage companies, consulting teams, or investment platforms.