Data Specialist

About the role 

We are looking for a Data Specialist to own the data layer of our fundamental Equity AI project.

You will be responsible for sourcing and evaluating data of every kind (alternative, fundamental, market, internal), deciding what to buy, crawl, or build, owning our relationships with data and AI vendors, and shaping how that data is structured and delivered into research and AI workflows.

The ideal candidate has worked extensively with data vendors, or worked at one, and has spent time at a hedge fund or mutual fund, with a clear understanding of how investment teams use data. Prior work on AI projects and the ability to manage a team are a strong plus.

What you'll do

• Identify, evaluate, and prioritize data sources across the alternative, fundamental, and market data landscape, proactively surfacing the ones that are genuinely useful to the investment teams.
• Build and manage vendor relationships: trial negotiations, dataset evaluations, pricing, contract terms, and ongoing coverage.
• Develop a structured framework for dataset due diligence: data quality, coverage gaps, refresh frequency, licensing, and integration complexity.
• Work on demand: start from an internal request, or proactively identify a need worth solving, then screen the wider data universe and validate whether a dataset genuinely delivers that value.
• Acquire data through whichever route fits the need: purchasing from vendors, crawling web sources, and integrating the firm's own internal data.
• Integrate data from different sell-side providers and different reporting conventions, normalizing definitions so the numbers can be compared like for like.
• Set up early-stage ingestion pipelines and data infrastructure to make datasets usable for analysts and the AI platform (Python, SQL, standard APIs and SFTP); scale and hand off as the program grows.
• Partner with portfolio managers and analysts to understand what data is most valuable for fundamental Equity L/S research, and source or build toward those hypotheses.
• Identify and engage with emerging Chinese alt-data vendors, including those not yet well-known internationally.

What we're looking for

• 5+ years working directly with alternative data in an investment management, hedge fund, or alt-data vendor context, not just as a buyer, but as someone who has evaluated what works and built around it.
• Working domain knowledge of the hedge fund industry, gained at a China quantitative fund, a China long-only or mutual fund manager, or another Asian or global hedge fund.
• Breadth across the data families the desk depends on: alternative data, equity fundamental research data, and market data. Ideally you have worked hands-on with all three and understand how they complement each other.
• Hands-on experience with major financial data vendors such as Bloomberg, FactSet, and Wind, including a practical view of where each is strong and where it falls short.
• Command of the full data lifecycle: licensing and purchasing from vendors, web crawling and scraped sources, and internal proprietary data. You know what each acquisition route costs in money, legal exposure, and maintenance, and how to process the different source types (structured, semi-structured, and unstructured) into something research can use.
• Fluency with the connectivity layer: REST APIs, SFTP and bulk file feeds, vendor SDKs, and agent-facing interfaces such as MCP (Model Context Protocol). Ideally you have already wired multiple sources through these connectors into an AI agentic workflow.
• A genuine track record of finding or operationalizing data that contributed to investment insight, and you can point to specific datasets and explain why they worked or didn't.
• Strong vendor and relationship network across the Asia alt-data ecosystem; familiarity with Chinese-market specific data providers.
• Sufficient data engineering depth to bootstrap pipelines independently: Python, SQL, REST/SFTP ingestion, and basic data modeling. You do not need a separate engineer to translate your ideas into working data flows.
• Sharp instincts for distinguishing signal from noise, and for how a dataset degrades or gets crowded over time.
• Ability to communicate clearly with PMs and analysts, translating data observations into investment hypotheses and back.

Nice to have

• Understanding of data and AI workflows: how datasets are prepared for model and agent consumption, retrieval and context assembly, and how AI tooling changes what a data platform needs to deliver.
• Prior experience in a research role, or close collaboration with fundamental analysts.
• Previous experience at a single-CIO hedge fund, a China quantitative hedge fund, or a China mutual fund.
• Previous data engineer or data analyst experience at an alternative data provider, for example BigOne Lab (百观科技), YipitData, Consumer Edge, Sandalwood Advisors, UBS Evidence Lab, or RanShu (燃数).

Requirements and availability

• Fluent English is required. Additional languages, particularly Mandarin and Cantonese, are a plus given the Chinese-market sources and vendors this role covers.
• Prior experience in the financial industry is required. We are not considering candidates without a financial industry background.
• Any non-compete must be 6 months or less.
• Candidates able to start within 1-2 months are strongly preferred.