Data Operations

Simile

4d•$200,000 - $300,000

About The Position

Simile is seeking a Data Operations professional to join their team. This role is critical as it sits upstream of research, engineering, and customer deployments, influencing decisions about which populations can be simulated, which datasets to acquire, and the fidelity of agent representation. The Data Operations team is small, high-ownership, and works closely with researchers and customers. As a member of Data Operations, you will be responsible for the entire data lifecycle at Simile, from third-party licensing to first-party collection. This includes identifying and securing new datasets to expand simulation capabilities across new domains and geographies, and managing the supply chain for transforming raw data into grounded agents. Key responsibilities involve designing data collection instruments, managing vendor relationships, and ensuring the quality and representativeness of data to maintain simulation trustworthiness.

Requirements

Excitement about enhancing Simile's data supply chain and expanding global data partnerships.
Ability to build scalable processes and manage multiple threads simultaneously, ensuring clear documentation of decisions.
Intuition for identifying valuable datasets, negotiating exclusivity clauses, and knowing when to seek alternatives.
Negotiating experience or aptitude, with the ability to be effective in situations with limited leverage.
Comfort with analyzing data, understanding data biases, sample selection, data schema trade-offs, collection strategies, and defining data quality.

Nice To Haves

Consulting or investing experience, with a track record of tackling complex, ambiguous problems and strong first-principles problem-solving skills.
Procurement experience, including contract negotiation with vendors and managing competing requests.
Technical fluency, with the ability to use coding agents for checks and workflow automation.

Responsibilities

Expanding Simile's coverage of the world by identifying and acquiring data for new populations and geographies.
Running and expanding the operations behind Simile's human data collection, including panel and field vendor management, incentive structures, throughput, and cost per participant.
Identifying and structuring agreements for the richest datasets to improve simulation, focusing on terms suitable for foundation models.
Building an always-on feedback loop by translating research and deployment needs into a data sourcing roadmap and tracking data's impact on the model.
Defending data fidelity by setting standards for sample composition and response quality, detecting fraud and low-effort participants, and ensuring data credibility.
Ensuring trust and compliance by working with legal on consent, privacy, and usage rights for enterprise and government partners.