Go-To-Market Recruiter
Hippocratic AISalary not specified
Full Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Not SpecifiedCompensation
N/AExperience Level
N/AJob Type
Not SpecifiedVisa
N/AIndustries
Requirements
- 2–3 years recruiting within technical ecosystems (data, dev ops, infrastructure, AI/ML) with proven success
- 8+ years of recruiting experience in B2B SaaS, with a minimum of 3+ years dedicated to GTM roles
- Experience recruiting in a startup or high-growth environment
- Proven ability to use data and insights to influence hiring decisions and optimize recruiting processes
- Strong relationship-building and communication skills, with the ability to influence stakeholders at all levels
- Track record of consistently delivering high-quality hires against ambitious hiring goals
Responsibilities
- Own the end-to-end recruitment process from sourcing to offer, delivering a seamless and exceptional candidate experience
- Partner with GTM leaders and hiring managers to understand business needs and develop hiring strategies that drive company goals
- Build trusted relationships across teams, providing data-driven insights and regular updates on hiring progress
- Source, assess, and close top talent for GTM roles, with a particular focus on candidates from data, dev ops, infrastructure, and AI/ML ecosystems
- Develop and execute innovative sourcing strategies to engage passive talent
- Maintain a forward-looking talent pipeline, ensuring the business is well-positioned to meet both immediate and long-term hiring needs
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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