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Requirements:
Proven enterprise SaaS sales experience, consistently exceeding quota in complex, multi-stakeholder deals.
Proven success selling data platforms, operational databases (e.g., Postgres, MySQL, cloud-native DBaaS), or adjacent data/AI infrastructure to technical buyers and business leaders.
Strong understanding of modern data and application architectures, including cloud-native services, microservices, event-driven systems, and how operational data underpins AI and analytics strategies.
Ability to sell to both technical stakeholders (developers, architects, data engineers) and business stakeholders (product leaders, operations, line-of-business owners).
Demonstrated experience leading specialist or overlay motions, working jointly with core Account Executives to create and progress opportunities.
Executive presence with the ability to whiteboard architectures, lead C-level conversations, and build trust with senior decision makers.
Strong value selling skills: adept at discovering pain, building a business case, and tying technical capabilities to clear, quantified outcomes.
Excellent communication, storytelling, and negotiation skills, with comfort presenting to both large and small audiences.
Bachelors degree or equivalent practical experience.
Preferred qualifications
Experience selling Postgres, operational databases, OLTP workloads, or transactional cloud database services, ideally within large or strategic accounts.
Familiarity with data platforms, lakehouse architectures, and cloud ecosystems (AWS, Azure, GCP), including how operational databases fit within broader data and AI strategies.
Understanding of reverse ETL, real-time decisioning, and operational analytics use cases, and how they drive value for customer-facing and internal applications.
Exposure to AI-native and agent-driven applications that depend on low-latency, highly scalable operational data services.
Prior experience in a high-growth, category-creating environment, helping shape new plays, messaging, and customer narratives.
Experience collaborating with partners and ISVs to drive joint pipeline and co-sell motions.

Requirements:
Strong software engineering fundamentals (from coding to system design).
Strong product and customer mindset, you care about UX, edge cases, and real user outcomes.
Deep proficiency with AI development tooling and a passion for using AI as a true productivity multiplier.
Ownership mentality and the ability to execute independently within a small team.

Requirements:
Requirements

8+ years of experience in Data Science, Machine Learning, Statistics, Operations Research, Economics, or a related field.

Proven experience leading Data Science teams.

M.Sc. or Ph.D. in a quantitative discipline.

Strong expertise in machine learning, predictive analytics, optimization, forecasting, and statistical modeling.

Experience in fintech, revenue optimization, forecasting, recommendation systems, retail technology, or similar data-intensive domains.

Strong business orientation and ability to connect analytical insights to business outcomes.

Excellent communication and stakeholder management skills.

Experience working in a SaaS environment.

Fluent English.


Advantage

Experience with Generative AI and LLM-based applications.

Experience working with enterprise customers.

Experience managing distributed teams.

Requirements:
+5 years of experience in a similar operations, finance, or people-ops role
Strong analytical and Excel skills - comfortable with analyzing data across multiple sources
Excellent written English and the ability to communicate clearly with US-based vendors and partners
Highly organized, detail-oriented, and able to manage multiple concurrent priorities across finance, operations, and HR
Experience working directly with senior leadership and taking ownership with a high degree of autonomy.
Comfortable learning new processes and systems quickly
Startup experience - a strong advantage