Full-Time

Head of Demand Generation

Confirmed live in the last 24 hours

Kumo

Kumo

51-200 employees

Generates and deploys predictive models

Fintech
AI & Machine Learning

Senior

Mountain View, CA, USA

This is an onsite role at the Mountain View headquarters.

Category
Growth Marketing
Growth & Marketing
Required Skills
Hubspot
Salesforce
Data Analysis

You match the following Kumo's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • 5+ years of experience in demand generation or growth marketing, preferably in SaaS, AI, or data analytics industries.
  • Proven ability to design and execute campaigns that generate measurable pipeline and revenue.
  • Expertise in high-quality list building and targeting.
  • Strong collaboration skills, with experience working closely with senior leadership and GTM teams.
  • Fluent in customer marketing strategies to cultivate reference customers and drive advocacy.
  • Proficiency with marketing automation tools (e.g., Marketo, HubSpot) and CRM platforms (e.g., Salesforce).
  • Highly analytical and results-oriented, with a strong focus on ROI and metrics-driven decision-making.
Responsibilities
  • Build and maintain highly actionable prospect lists that align with Kumo’s Ideal Customer Profile (ICP), supporting targeted marketing and sales initiatives.
  • Design and execute exceptional campaigns tailored to specific regions, accounts, personas, and use cases. Leverage all available marketing channels—direct, digital, and channel partners—to drive demand and build pipeline.
  • Work closely with the CEO, co-founders, and senior GTM leaders, including Sales and Customer Success, to refine and accelerate revenue strategies. Provide insights and recommendations to align demand generation initiatives with company-wide priorities and objectives.
  • Develop and implement strategies to cultivate reference customers, supporting both account expansion and new logo acquisition. Build programs that enhance customer advocacy and showcase Kumo’s impact in real-world applications.
  • Oversee marketing operations to ensure seamless campaign execution and data-driven decision-making. Monitor and analyze campaign performance, delivering actionable insights to optimize conversion rates, pipeline growth, and ROI.
  • Maintain a relentless focus on driving pipeline and revenue growth, balancing strategic planning with hands-on execution. Build scalable processes that enable consistent delivery of high-impact campaigns aligned with Kumo’s business goals.

Kumo.ai specializes in creating and implementing accurate predictive models for organizations that need reliable forecasts for critical operations. Their platform uses Graph Neural Networks to analyze raw relational data, which removes the need for manual data preparation and enhances prediction accuracy and efficiency. Unlike many competitors, Kumo.ai's platform streamlines the entire Machine Learning lifecycle, from data preparation to model deployment, while also optimizing costs by eliminating unnecessary infrastructure. The goal of Kumo.ai is to provide a fast return on investment for its clients, which range from small businesses to large enterprises, by offering flexible deployment options and ensuring high service availability.

Company Size

51-200

Company Stage

Series B

Total Funding

$35.5M

Headquarters

Mountain View, California

Founded

2021

Simplify Jobs

Simplify's Take

What believers are saying

  • Kumo's $18M Series B funding will expand its platform and market reach.
  • Integration with Snowpark Container Services enhances deep learning capabilities within Snowflake Data Cloud.
  • Kumo's platform supports both SaaS and Private Cloud models, offering client flexibility.

What critics are saying

  • Increased competition from Databricks' Marketplace may divert potential customers.
  • The rise of multimodal AI could overshadow Kumo's current offerings.
  • Rapid AI advancements by tech giants may set new industry standards Kumo must meet.

What makes Kumo unique

  • Kumo.AI uses Graph Neural Networks for predictive modeling, eliminating manual feature engineering.
  • The platform offers a SQL-like Predictive Querying Language for rapid AI model creation.
  • Kumo.AI integrates with Snowflake's Native App Framework, enhancing model performance and scalability.

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Benefits

Stock Options

Medical Insurance

Dental Insurance

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-5%

2 year growth

1%
PR Newswire
Jun 4th, 2024
Kumo Ai Launches Snowflake Native App In Snowflake Marketplace

Data scientists can build highly accurate predictive AI models faster with Kumo AISAN FRANCISCO, June 4, 2024 /PRNewswire/ -- Today at Snowflake Data Cloud Summit 2024 , Kumo AI , a leader in predictive AI, announced it has launched Kumo as a Snowflake Native App in Snowflake Marketplace in private preview. Kumo helps data scientists build highly accurate machine learning (ML) models that better predict user and customer behavior by combining graph learning over enterprise data with generative AI models trained on public data. Kumo's Snowflake Native App is available through Snowflake Marketplace, can be paid for with Snowflake Capacity commitment for eligible customers, and is built using the Snowflake Native App Framework, enabling data scientists to develop predictive models faster than ever before."We understand how difficult building high-performing ML models can be. Our partnership with Snowflake simplifies the process and eliminates many of the typical hurdles that data scientists experience," said Vanja Josifovski, co-founder and CEO of Kumo AI. "By coupling Snowflake's well-known scalability, speed, and reliability with Kumo's specialized AI to identify and maximize the signal hidden in Snowflake data, we can produce highly accurate predictive ML models that are based on the entirety of your data including multiple relational tables, text, and images. Joint customers can unlock the full potential of their Snowflake data to fuel data-driven decisions and make granular predictions such as personalized recommendations."Businesses are trying to maximize revenue-impacting KPIs like conversion, cart size, and retention rates using insights uncovered from historic data, but struggle with efficient approaches and significant model improvements

PYMNTS
May 20th, 2024
Openai, Google Double Down On Multimodal Ai In High-Stakes Chatbot Race

In the cutthroat world of artificial intelligence, tech behemoths are betting big on a new frontier: multimodal AI. As the shine of text-based chatbots dims, companies are gambling that the future belongs to AI assistants capable of seeing, hearing and conversing with users more naturally and intuitively. The battle for AI dominance has taken on a new dimension, with “multimodal” emerging as the latest buzzword. “The usefulness of multimodal AI comes from its ability to simultaneously process and analyze diverse types of data, such as text, images, audio and video,” ComplyControl Chief AI Officer Mikhail Dunaev told PYMNTS

Payment Expert
Mar 8th, 2024
Google, Meta And Openai Urge Participation In Ai Development

Credit: cono0430, ShutterstockAn open letter signed by a range of big and small tech companies has committed to responsible development of Artificial Intelligence (AI) at a time of increased public focus on the technology. Four of the the most high-profile signatories of the letter are Google, Microsoft, Meta and OpenAI, four of the most influential firms in global AI products – the latter is notable for being the creator of widely used AI platform ChatGPT. Due to continued development, AI has become increasingly utilised for business purposes, such as automation of general day-to-day tasks, risk management, anti-money laundering and fraud prevention

Yahoo Finance
Nov 16th, 2023
Kumo.Ai Unveils New Predictive Ai Platform Featuring Sql-Like Predictive Querying Language

MOUNTAIN VIEW, Calif. , Nov. 16, 2023 /PRNewswire/ -- Kumo.AI , a Sequoia Capital-backed predictive AI company, announced the general availability of its Kumo.AI platform, enabling rapid creation and deployment of state-of-the-art AI models on private enterprise data. AI practitioners can now use Kumo.AI's intuitive SQL-like Predictive Querying Language to build multiple task-specific AI models in a single day. Founded in 2021 by Stanford University Professor (Jure Leskovec) and former Airbnb and LinkedIn executives (Vanja Josifovski, Hema Raghavan), Kumo.AI helps enterprises unlock customer-focused use cases, such as personalization, churn and LTV prediction, fraud detection, and forecasting.Kumo, cutting edge AI that can query the future (PRNewsfoto/Kumo.AI)While generative AI excels at natural language understanding and generation, it lacks the capability to perform more complex, enterprise-specific tasks, such as predicting customer behavior or detecting fraudulent transactions. Kumo.AI is the first platform that bridges this gap by applying deep representation learning, a technology behind the current AI revolution, to enterprise data in data warehouses

VentureBeat
Jun 27th, 2023
Kumo Empowers Deep Learning In Snowflake Data Cloud Through Snowpark Container Services

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More. Kumo, a deep learning platform for relational data, announced today at Snowflake Summit 2023 its integration of deep learning capabilities directly into the Snowflake Data Cloud through Snowpark Container Services.Snowflake’s recently introduced Snowpark Container Services expands the functionality of Snowpark. This update allows organizations to run third-party software and full-stack applications within their Snowflake accounts.According to Snowflake, with this integration customers can maximize their data potential by using cutting-edge tools while maintaining data security and eliminating the need for data movement.Moreover, Snowpark Container Services includes GPU support, which gives data science and machine learning teams a way to accelerate development and bridge the gap between model deployment and consistent data security and governance throughout the AI/ML lifecycle.