• Analyze data to identify trends, patterns, and anomalies. • Support root cause analysis and performance investigations. • Assist in KPI tracking, data quality checks, and governance processes. • Build and maintain business intelligence reports and apply statistical analysis fundamentals. • Write and maintain SQL queries using joins, CTEs, and window functions. • Help enhance and maintain scenario models under guidance. Track and report on forecast accuracy. • Build and maintain dashboards and standard reports.

• Conduct advanced data analysis, mining, and trend identification to surface meaningful business insights. • Develop and maintain KPIs, performance management frameworks, and data quality standards. • Perform root cause analysis, statistical hypothesis testing, and predictive and prescriptive analytics. • Own data governance and quality assessment practices. • Write and optimize complex SQL queries using CTEs, window functions, joins, and stored procedures. • Design and maintain data models, ETL/ELT pipelines, and data warehouse structures. • Perform data validation, reconciliation, and transformation to ensure analytical accuracy. • Measure and continuously improve forecast accuracy using trend analysis, seasonality analysis, and statistical methodologies. • Develop scenario models to support strategic decisions. • Design executive dashboards, scorecards, and interactive reports that tell a clear story. • Own QBR preparation and deliver findings directly to senior leadership, including the executive team. You will translate analytical work into business narratives that influence real decisions at the company level. • Build automated reporting solutions that scale across the organization. • Partner with stakeholders to gather requirements, document processes, and align on priorities. • Present technical analysis to C-suite leaders as business narratives and strategic recommendations. • Facilitate meetings, lead cross-functional collaboration, and support change management initiatives.

• Own recurring reporting for User Operations — weekly, monthly, and QBR-ready — tailored to ops, leadership, and cross-functional audiences • Translate support data into clear narratives: what's happening, why, and what to do about it • Track and maintain north star metrics: cSAT, TTR by tier, QA scores, bug escalation rate to EPD, and First Response Time • Build and maintain self-serve dashboards that give the ops team and leadership real-time visibility into support performance • Partner with Support Systems to ensure Zendesk is instrumented to capture the data we need • Work with Harvey's central data team to connect support data to broader product and customer data sources • Identify and close data collection gaps — if we can't measure it, help define how we should • Design feedback loops that connect support signals to Product, Engineering, and Customer Success • Quantify the operational cost of product bugs, feature gaps, and onboarding failures • Contribute to QA analytics as the QA program matures • Track ticket deflection, AI/chatbot performance, and self-service effectiveness • Measure the impact of AI-driven support — containment rate, escalation rate from AI interactions, resolution quality — and surface findings that drive how we tune and invest in those tools • Support ad hoc analytical requests from the Support Operations Manager, User Operations leadership, and senior stakeholders

• Responsible for the generation and analysis of marketing data for the purpose of translating data into information that will be used to demonstrate insight that drives marketing performance and investment decisions. • Builds and maintains dashboards and reporting frameworks that track marketing performance across marketing programming, including but not limited to pipeline contribution, conversion, and return on investment. • Analyzes data across multiple systems (Customer Relationship Management or CRM), marketing automation, web analytics, and digital platforms, to identify patterns, trends, opportunities, and risks. • Translates complex data into clear, concise insights and recommendations that influence marketing strategy and investment decisions. • Partner with channel strategy and marketing operations to inform prioritization, campaign optimization, and performance tradeoffs. • Develop and evolve measurement approaches including attribution, funnel analysis, and campaign performance frameworks. • Ensure data quality, consistency, and alignment of key metrics across systems and stakeholders. • Support planning and performance reviews (quarterly, annual) with data‑backed insights and recommendations. • Deliver ad hoc and deep‑dive analyses to support campaigns, lifecycle programs, and go‑to‑market initiatives. • Other duties as assigned.