Job Description
Data Analyst/Engineer
Jain Global, LLC
Jain Global is an innovative multi-strategy investment firm founded in July 2024 by Bobby Jain with over 400 employees operating from offices in New York, Houston, London, Singapore, and Hong Kong, we are looking to add to our growing teams.
Role Overview
As a scientifically minded Data Analyst/Engineer, you will be a member of the team responsible for delivering the data that enables the growing number of portfolio managers to research, test, execute and manage their investment strategies with ease and confidence, which is crucial to the firm’s success and growth.
You will be sourcing, analyzing, cleaning and curating vendor datasets and integrating them seamlessly with other datasets in the Data Platform to increase the data’s business value, including value through platform effects. This will enable portfolio managers, Quants and risk managers to focus on using high quality data instead of wrestling with problematic raw data, thus increasing their productivity.
You have worked in or with financial industry Front Office businesses. You thrive on diving deep into data, understand its business value and how to improve datasets to increase that value. You are curious and take a meticulous scientific approach to analyze and test data and thus ensure that the data sets you deliver add real value to the various business units.
Responsibilities
- Curate customer‑centric data products: Collaborate with customers to understand their specific needs across trading, cross‑referencing market & alternative data, aggregation of fungible assets, researching & backtesting strategies. Source the relevant data, analyze, clean and enrich it at the pace demanded by hedge fund operations. Iterate with the customers to increase the data’s value and collaborate with the Data Platform team to maximize platform effects and the utility for the entire firm. Initial focus is on Equity identifier mappings (SecMaster) and Corporate Actions, beyond that all asset classes and data types are in scope.
- Implement automated Data Quality checks to guarantee the high quality that increases the raw data’s value can be relied upon all the time, and any deviation from quality expectations are immediately noticeable. Automate monitoring and alerting to ensure any issues are dealt with immediately with minimal business impact.
- Interact with data vendors: Manage data vendor relationships to understand the nuances of their data products, and how we can extract maximum value from their data.
- Role‑model continuous improvement: Maintain high standards of analytical excellence, ownership and customer care. Mentor junior analysts and help hire new talent. Streamline workflows, improve data quality, and efficiency to support faster insights and improved decision‑making by our customers.
Qualifications & Experience
- BSc/MSc/PhD in Computer Science, Physics, Engineering or similar and 3+ years financial industry experience in Front Office / Quant / organisations or on a PM desk, preferably with some time spent in a hedge fund.
Technical Skills
- Expert level data analysis / science skills in Python and familiarity with Pandas/Polars/Snowpark data frames. Experience in other languages such as C#, F#, C++ or Java is a plus.
- Advanced SQL skills are needed. Experience with modern data storage & querying technologies (e.g. Snowflake, Redshift, BigQuery), and/or file formats (e.g. Parquet and Iceberg) is desirable.
- Familiarity with Linux environments, git and modern DevOps approach.
- Demonstrated experience in test automation to maintain high standards and a fast rate of change with confidence.
- Familiarity with monitoring production systems using modern observability & alerting solutions (e.g. Grafana/Prometheus, DataDog, ELK) is desirable.
- Hands‑on experience with data pipeline orchestration tools, e.g. Airflow, and data download mechanisms, e.g. sFTP, various vendor APIs is helpful.
- Financial Data: Deep understanding of market and reference data, ideally across a broad range of asset classes, but at least Equity identifiers and Corporate Action datasets. Clear understanding of how data adds value to a hedge fund’s business, and how that value can be increased.
Soft Skills
- Effective communication skills with Front Office stakeholders and Tech colleagues, curiosity, a scientific and collaborative mindset, ability to produce in an agile environment.
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