5 дней назад
Data Analyst (Data MarketPlace)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Analyst (Data MarketPlace) (Financial Data/Python/SQL): Assessing external and internal datasets for commercial value, quality readiness, and MarketPlace inclusion while creating new datasets from MSCI data with an accent on exploratory analysis, data profiling, and methodology design. Focus on validating messy financial datasets, prototyping derived datasets, and handing methodologies to Technology for production-scale automation.
Location: London, City of London, United Kingdom
Company
provides research-based financial data, analytics, indexes, and technology for investors and participants across the global financial ecosystem.
What you will do
- Perform first-pass analysis of external vendor and internal datasets to assess commercial value, coverage, structure, history, frequency, and quality readiness.
- Document concise value-and-quality assessments, identify risks and gaps, and validate datasets already offered through the Data MarketPlace.
- Collaborate with Data Scout, Applied Research, Technology QA, Research, and product heads across Index, Analytics, S&C, and Private Assets.
- Generate dataset analytics such as summary statistics, coverage charts, and illustrative use cases for the platform and marketing newsletter.
- Explore internal data, aggregate and combine sources, and derive new datasets for product and client opportunities.
- Define and validate prototype methodologies before handing them to Technology for scaling, automation, and operationalisation.
Requirements
- 3–5+ years of experience in data analysis, data science, or quantitative data roles, ideally in financial data or asset management.
- Strong Python and SQL skills, including experience manipulating large, wide, and messy datasets with pandas and relational databases.
- Experience with data cleaning, validation, quality assurance, and exploratory data analysis.
- Knowledge of financial data concepts including instruments, identifiers, corporate actions, time series, and point-in-time data.
- Strong attention to detail and judgement when assessing data quality and proving suspected issues.
- Comfort using AI and LLM tools for data exploration and profiling.
Nice to have
- Familiarity with data, Barra factor and risk models, indexes, ESG, climate data, or comparable provider datasets.
- Experience with Snowflake, Databricks, GCP, or data-pipeline tooling.
- Exposure to backtesting or signal research on financial datasets.
Culture & Benefits
- Flexible working arrangements and collaborative workspaces.
- Comprehensive benefits and compensation schemes tailored to the employee’s location.
- Learning opportunities through the Global Orientation program, Learning@, AI Learning Center, LinkedIn Learning Pro, and tailored development programs.
- Professional growth through internal mobility, expanded roles, and multi-directional career paths.
- Inclusive environment supported by multiple Employee Resource Groups.
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