Data Analyst — Data MarketPlace

Responsibilities The Data Analyst works hands-on with the datasets that feed the MSCI Data platform . The role has two primary purposes. First, to perform crude, first-pass analysis on datasets before integration — assessing their basic commercial value and quality readiness — so the team can decide quickly and confidently whether a dataset is worth  onboarding . Second, to act as a quick-response team that creates new datasets from MSCI internal data: extracting value, aggregating and deriving novel datasets, an d authoring the first working version of the  methodology  before partnering with Technology to scale and automate it. This is exploratory, judgement-led work that sits ahead of the formal data pipeline; production-grade validation and automation are owned by the QA and engineering teams in Technology, with whom the Analyst works closely.     Your Key Responsibilities   Pre-integration value & quality assessment     Perform crude, first-pass data analysis on external vendor datasets before integration, to assess their basic commercial value and quality readiness.   Assess internal MSCI datasets for quality and readiness ahead of inclusion in the   MarketPlace .   Explore and   profile datasets — coverage, frequency, history,   schema   and obvious quality issues — enough to support a   fast onboarding   decision.   Document a concise value-and-quality readiness view per dataset, flagging the key strengths,   gaps   and risks.   Validate the datasets already offered on   the   MarketPlace   on an ongoing basis, confirming they   remain   accurate ,   current   and as described.     Collaboration & promotion     Work closely with the Data Scout to evaluate   candidate   external datasets early in the sourcing process, so commercial and quality views are joined up.   Work with Applied Research to understand what makes a dataset valuable for   backtesting   and signal   work, and   feed that lens into assessments.   Work with the Technology QA team, handing over assessed   datasets   and informing the automated validation checks they build and own.   Contribute to the development and promotion of the   MarketPlace   by generating per-dataset analytics — summary statistics, coverage charts, illustrative use cases — for the marketing newsletter and the platform.     New dataset creation from internal data     Act as a quick-response team to explore MSCI internal data and rapidly extract value where there is a clear product or client opportunity.   Aggregate, combine and derive new datasets from existing internal data, prototyping the output before any heavy engineering investment.   Author the first working version of the   methodology   to aggregate and construct each new dataset — the reference definition that Technology then   productionises .   Work with the Research team and the relevant product heads (Index, Analytics, S&C, Private Assets) to shape new datasets that have product relevance, settle the right methodology early, and ensure the output is useful to the teams who will build on it.   Validate the prototype dataset and   methodology , then hand over to Technology to scale, automate and   operationalise .   Your skills and experience that will help you excel 3 -5 + years in a data analyst, data   science   or quantitative data role, ideally within financial data or asset management.   Strong Python and SQL skills; comfortable manipulating large,   wide   and messy datasets ( e.g.   pandas, relational databases).   Demonstrated experience in data cleaning,   validation   and quality assurance.   Strong exploratory data analysis skills — able to quickly make sense of an unfamiliar dataset and form a view on its value and quality.   Comfortable using AI / LLM tools to speed up exploration and profiling (the production validation automation is owned by Technology QA, but familiarity with these tools is a plus).   Solid