Explorium

Education Requirements:

• Bachelor’s or Master’s degree in Engineering, Data Science, Business, or a related field.

Experience Requirements:

• 5+ years of Product Management experience, ideally in a data-first company where data is the product.

• Strong customer-facing product experience, including discovery and translating needs into scalable solutions.

• High technical fluency and ability to work effectively with data developers, data scientists, and engineering teams.

• Experience building or managing data products used by AI agents, autonomous systems, or LLM-driven workflows.

• Proven ability to define product success metrics and track KPIs such as adoption, impact, accuracy, and coverage.

Other Requirements:

• Strong analytical mindset and experience using data to drive prioritization and roadmap decisions.

• Excellent communication and stakeholder management skills in a global, cross-functional environment.

Responsibilities:

• Own the strategy, vision, and roadmap for Explorium’s external data products.

• Lead customer discovery and translate insights into scalable product initiatives, requirements, and clear delivery plans.

• Drive prioritization across competing needs, balancing customer value, business impact, feasibility, and time-to-market.

• Lead the end-to-end data product lifecycle: discovery, definition, delivery, launch, adoption, and continuous improvement.

• Collaborate cross-functionally with Data Science, Engineering, Sales, CS, and Partnerships to validate use cases.

Experience Requirements:

• 3+ years of industry experience with building data-intensive platforms

• 3+ years of hands-on experience programming in Python

• Experience with working with complex data sets

• Experience with Databases, SQL and NoSQL, and Data modeling

• Experience working with cloud compute and storage services on AWS/GCP/Cloudflare

Other Requirements:

• Experience with TypeScript programming - advantage

• Experience with building Machine Learning models - advantage

• Experience with building with LLMs or transformer models - advantage

• Experience with designing data lakes - advantage

• Experience with building MCP servers - advantage

Responsibilities:

• Design and implement complex end-to-end data pipelines including data extraction, feature engineering, data quality and data serving

• Work with Large Language Models and AI agents to deliver high scale, high quality features for customers

• Build and maintain MCP servers and AI application infrastructure

• Take ownership of a true research project from POC to production

• Contribute to a wide variety of projects using a range of technologies and tools

Benefits:

• Equity compensation in addition to cash compensation.

• Competitive medical, dental, and vision insurance plans.

• Paid parental and maternity leave.

• Unlimited PTO.

• A fantastic company culture that prioritizes teamwork and growth.

Experience Requirements:

• 6+ months of client-facing sales or business development experience in a B2B environment with a record of success.

• Excellent verbal and written communication skills, with the ability to lead executive-level discussions.

• Proven track record of creative, persistent, and effective outbound sales lead follow-up messaging.

• Consistent history of exceeding sales targets.

• Strong commitment, attention to detail, organizational skills, and multitasking abilities.

Other Requirements:

• Self-starter, comfortable with limited supervision, and adaptable to a multi-cultural startup environment.

• Prior outbound and inbound SDR/BDR experience.

• Previous experience at a high-growth SaaS company.

• Proficiency with Salesforce, Salesloft, LinkedIn, Outreach, Claude, Perplexity, and OpenAI (or similar tools).

• Strong focus on achieving goals.

Responsibilities:

• Become an expert in Explorium’s solutions, serving as the initial point of contact for many sales prospects.

• Identify new organizations and stakeholders that align with Explorium’s buyer and customer personas.

• Consistently and professionally follow up with leads through cold outreach (email, phone, and LinkedIn).

• Collaborate with Account Executives to schedule qualified meetings and build the sales pipeline.

• Meet or exceed assigned sales goals while fostering cooperation and sharing best practices.