Dataset Enablement Manager(Frontier Sciences & Math)

Employer description and requirements

About Turing

Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM, and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.

Role Overview

We are seeking a Dataset Enablement Manager to bridge the technical gap between scientific data pipelines and centralized commercial teams. In this role, you will package complex technical datasets into high-impact collateral, educate client-facing teams on domain-specific benchmarks, and drive the multi-client sell-through of our OTS dataset portfolio to leading global AI labs.

Requirements

Experience: 6+ years of professional experience in technical enablement, pre-sales engineering, technical product marketing, or applied research consulting.

Domain Fluency: Strong conceptual understanding of scientific benchmarks, algorithmic problem-solving, and the mechanics of LLM reasoning/evaluations.

Communication: Exceptional, near-native English verbal and written communication with a demonstrated track record working with US-based engineering leaders, research scientists, and commercial teams.

Responsibilities

Pipeline Tracking: Maintain deep, real-time visibility into active dataset pipelines across all frontier science and math teams.

Collateral & Sample Packaging: Collate sample packs, technical collateral, schema definitions, and benchmark comparisons to clearly communicate dataset value.

Commercial Enablement & Training: Coordinate regular deep-dives for client-facing teams, introducing new offerings and highlighting customer value propositions.

Sell-Through Performance Tracking: Drive multi-client monetization, identify under-utilized datasets, and track/report on sell-through performance metrics.

Education & Experience

Bachelor’s or Master’s degree in Mathematics, Physics, Chemistry, Computational Biology, Computer Science, or a related discipline.

Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred but not required.

Offer Details:

Commitments Required: at least 4 hours per day and upto 40 hours per week with 4 hours of overlap with PST.

Engagement type: Contractor

Engagement Length: 8 weeks

Evaluation Process -

Shortlisted candidates will be sent a Job Interest Form.

Final selected candidates will be contacted with the next steps and onboarding requirements.