Associate Manager - GTM Analytics, Insights and AI

Associate Manager - GTM Analytics, Insights and AI

Kore.ai is a globally recognized leader in the conversational and generative AI space helping enterprises deliver extraordinary experiences for their customers, employees, and contact center agents. Kore.ai’s goal is to empower businesses with effective, simple and responsible AI solutions that create engaging interactions. sectors serving over 100M of consumers and 500,000+ employees worldwide. With billions of interactions automated using our AI-powered technology, we have been able to save over $500M for these companies.

Kore.ai is one of the fastest-growing AI companies globally. We are recognized as a leader by the leading technology and industry analysts like Gartner, Forrester, IDC, ISG, Everest, and others.

Founded in 2014 by serial successful entrepreneur, Raj Koneru, Kore.ai supports customers globally across offices in Orlando, Hyderabad, New York, London, Germany, Dubai Frankfurt, Tokyo and Seoul.

We’re reshaping the way companies harness the power of AI, simplifying and enhancing accessibility. Work alongside some of the brightest minds in the industry to pioneer safe, reliable solutions. Join the Kore.ai team and help companies of all sizes simplify the adoption of advanced AI solutions responsibly.

POSITION / TITLE:

Associate Manager – GTM Analytics, Insights and AI

Role Overview

We are seeking an analytical, business-oriented Associate Manager of GTM Analytics, Insights and AI to help optimize the performance, efficiency, and scalability of our go-to-market organization. This role sits at the intersection of data analytics, business intelligence, strategic insights, and AI-driven innovation, translating complex data into actionable recommendations that improve revenue performance and inform business decisions.

This individual will own key analytical workstreams, sales productivity, customer and product performance, and GTM effectiveness. Beyond reporting historical performance, the role will proactively investigate business trends, identify root causes of performance gaps, and recommend actions to improve outcomes.

The ideal candidate combines strong analytical and technical capabilities with commercial acumen, intellectual curiosity, and the ability to communicate complex findings in a clear, concise, and compelling manner. One is comfortable moving between detailed analysis and strategic business discussions, operates effectively in ambiguous environments, and consistently translates insights into measurable business impact.

Key Responsibilities

1. GTM Analytics, Data Engineering and Business Intelligence
2. Develop and maintain a comprehensive view of GTM performance across Sales, Marketing, Customer Success, and other revenue-generating functions.
3. Build, maintain, and continuously improve executive dashboards (in Looker and Coefficient), operational scorecards, and self-service reporting solutions that provide timely and reliable visibility into business performance.
4. Build and maintain data pipelines, data models, and semantic layers that power GTM dashboards, forecasting models, and AI-enabled applications.
5. Own and evolve the GTM data model within the organization’s central data warehouse (ClickHouse), integrating data from CRM, sales engagement, customer support, and project management.
6. Write and optimize SQL and Python to extract, transform, validate, and analyze data across multiple sources.
7. Monitor key performance indicators, identify emerging trends and anomalies, and proactively surface risks and opportunities to business stakeholders.
8. Streamline recurring analyses through standardized reporting, reusable data models, and automation, reducing manual effort and improving analytical consistency.
9. Ensure analytical outputs are accurate, well-documented, easy to interpret, and aligned with established business definitions.
10. GTM Insights, Funnel Analytics, and Revenue Performance
11. Analyze the end-to-end GTM funnel, from demand generation and prospecting through opportunity creation, pipeline progression, revenue realization, customer retention, and expansion.
12. Evaluate pipeline generation, coverage, stage conversion, sales velocity, win rates, deal slippage, and sales cycle duration to identify the primary drivers of revenue performance.
13. Support the development of predictive and scenario-based analyses that improve pipeline planning, revenue forecasting, and resource allocation. 14….