[Remote] Senior Product Marketing Manager at Monte Carlo Data

San Francisco, California, United States

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Not SpecifiedCompensation

N/AExperience Level

N/AJob Type

Not SpecifiedVisa

N/AIndustries

Requirements

7+ years of product marketing experience, with at least 3 years in data infrastructure, analytics, AI/ML, or observability domains
Deep understanding of data pipelines, monitoring, data quality, lineage, model observability, and/or AIOps
Ability to translate complex technical concepts into business outcomes and vice versa
Proven ability to develop and articulate compelling narratives that differentiate technical products in competitive markets
Experience partnering with product management, demand generation, and sales in a fast-paced SaaS or cloud-native environment
Comfortable working with data-driven insights to measure and optimize go-to-market impact

Responsibilities

Develop and execute comprehensive GTM plans for data and AI observability products, including launch strategies, pricing insights, and competitive positioning
Craft differentiated product messaging that resonates with technical and business audiences — from data engineers and ML practitioners to CDOs and CIOs
Research and analyze market trends, customer needs, and competitor offerings in the data observability, AI observability, and MLOps ecosystems
Create sales tools, battlecards, and training materials to support field teams in communicating value and handling objections effectively
Collaborate with content, demand gen, and product teams to produce impactful assets — whitepapers, webinars, blogs, case studies, and presentations — that drive pipeline and awareness
Partner with customer success teams to identify champions, capture case studies, and highlight real-world impact stories
Serve as the voice of the customer to product and engineering, influencing roadmap decisions based on market insights

Skills

Monte Carlo Data

Provides end-to-end data observability solutions

About Monte Carlo Data

Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$229.6MTotal Funding

SERIES_DCompany Stage

Data & Analytics, AI & Machine LearningIndustries

201-500Employees

Benefits

Remote Work Options

Risks

Increased competition from Cribl and BigEye may impact market share.

Technical challenges in integrating with vector databases could affect performance.

New Chief Revenue Officer may lead to strategic shifts disrupting operations.

Differentiation

Monte Carlo offers end-to-end data observability for real-time data monitoring.

The platform integrates with tools like Slack, Teams, and JIRA for seamless communication.

Monte Carlo's root cause analysis speeds up data quality incident resolution.

Upsides

Growing demand for data observability tools boosts Monte Carlo's market potential.

Integration with vector databases opens new opportunities in AI model development.

Real-time data monitoring solutions are increasingly sought after by businesses.

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