Quant Developer

COMPANY PROFILE Greenland Investment Management is a Mumbai headquartered global hedge fund manager managing assets in excess of USD 1 billion. We manage one of the fifteen largest dedicated commodity hedge funds globally. We specialize in cross-market arbitrage strategies across commodities and currencies, investing globally across 40+ markets. We employ a purely quantitative approach using our proprietary big-data research systems to systematically create consistent alpha generating strategies. Our extensive network of globally connected exchange co-located servers along with our low latency trading platform allow us to algorithmically capture these market inefficiencies across asset classes.

About the Role We're hiring a Quant Developer to build and own the data and research infrastructure behind our commodities research team. You'll work across data engineering, research tooling, and trading-system integration — building pipelines, a backtesting framework, and the tooling that turns models into production-ready systems.

Responsibilities Market data • Design and maintain pipelines to ingest and process tick data across the commodities product universe. • Integrate additional third-party data vendors and own the maintenance of their APIs and feeds. • Store data efficiently in DuckDB and build/maintain spread series (calendar, inter-commodity, product). • Ensure data quality, completeness, and reliability through monitoring and validation. Research infrastructure • Build the research layer and a reusable, performant backtesting framework. • Improve the codebase so researchers use the system rather than write code — clean APIs, sensible defaults, minimal boilerplate. Trading system integration • Own the workflow for setting up research models on the trading system. • Build and maintain the scripts that push model parameters to the trading system reliably and repeatably.

Requirements • 2+ years as a quant developer, data engineer, or software engineer in a quant/trading environment. • Strong Python and SQL; production-quality, well-tested code. • Experience building data pipelines, ideally with tick-level market data. • Working knowledge of DuckDB (or similar columnar/analytical stores). • Solid grasp of time-series and financial tick data (gaps, timestamps, rolls/adjustments).