Investment Data Strategist (Research, Market Data & Replication)

Dynamic Beta investments, LLC•Greenwich, CT

22d•$180,000 - $250,000•Onsite

About The Position

DBi is a systematic hedge fund focused on hedge fund replication with a lean investment team. We are hiring an experienced professional to own the firm’s hedge fund performance and market data workflows, from external data providers through research, monitoring, and reporting. This role is designed for someone who understands how data quality, structure, and availability affect investment decisions, and who is comfortable working hands-on with modern data tools to support that goal. This is not a pure engineering role.

Requirements

Prior experience working with hedge fund, asset manager, or investment data
Direct exposure to hedge fund performance data and market data
Experience reconciling data across multiple performance or market data providers
Understanding of common biases and limitations in hedge fund and market data
Strong analytical and problem-solving skills
Python proficiency, including pandas for data analysis and manipulation & Streamlit or similar frameworks for internal reporting or dashboards
Strong SQL, including experience querying and designing data in SQL Server / Cloud data warehouses (Snowflake preferred)
Comfort working hands-on with data systems and reporting workflows

Nice To Haves

Experience with hedge fund replication, benchmarking, or factor-based strategies
Experience producing client-facing or investor-facing performance reports
Close collaboration with portfolio managers or investment teams
Comfort operating with high autonomy and ambiguity

Responsibilities

Ownership of hedge fund and strategy-level performance datasets sourced from multiple external providers
Reconciliation of data across vendors and vintages
Deep understanding of reporting lags, revisions, backfill bias, survivorship bias, and coverage gaps
Ongoing improvement of data quality, consistency, and interpretability
Ownership of market data used in replication, benchmarking, and diagnostics
Reasoning about market data quality, coverage, and edge cases
Ensuring consistency between historical market data used in research and data used in ongoing monitoring
Understanding how market structure and liquidity affect observed data
Working knowledge of futures markets, including contract specifications, rolls, expiries, and liquidity dynamics
Construction and maintenance of continuous futures time series, with awareness of roll methodologies and their impact on returns and signals
Understanding how contract rolls, gaps, and calendar effects influence historical analysis and live monitoring
Build and maintain performance and analytics reports for internal investment use and external distribution
Ensure reported results are accurate, consistent, and appropriately caveated
Translate complex data issues into clear, investment-relevant explanations
Resolve discrepancies between data providers and market sources
Treat data ambiguity and errors as investment and reputational risk
Ensure historical data used in analysis is comparable to live or ongoing reporting
Maintain and evolve internal data workflows supporting performance analysis and replication
Improve transparency, reliability, and efficiency of investment data processes
Propose pragmatic improvements grounded in investment impact rather than tooling preference