Investment Data Analyst

The Hollister Group; Massachusetts; On-site; USD 120,000 - 170,000; Full time

Job summary

The Hollister Group is hiring for an Investment Data Engineer who will own day-to-day investment data operations, including monitoring, triaging, and resolving data quality issues across security reference, pricing, corporate actions, and fundamentals. The role involves evaluating data from major vendors and ensuring accurate linkages across securities and identifiers.

You will collaborate with data engineers, researchers, and portfolio managers to define data behavior, build reconciliation

Qualifications

• Bachelor's degree in finance, economics, mathematics, computer science, or related field.
• Significant experience with investment data in institutional asset management or quantitative environments.
• Deep familiarity with major financial data vendors and how datasets are used in practice.
• Strong understanding of security reference data and identifier systems (SEDOL, CUSIP, ISIN, FIGI).
• Hands-on experience with corporate actions and their downstream implications.
• Proficiency in Python and SQL for data analysis and validation (Pandas, Polars, Dagster or similar).
• Ability to reason about data at both the record and portfolio level and investment implications.
• Experience building data quality, monitoring, or reconciliation frameworks.
• Working knowledge of systematic investment workflows (factor models, portfolio construction, execution).
• Strong cross-functional collaboration across engineering, research, and portfolio management.

Responsibilities

• Own day-to-day investment data operations, including monitoring, triaging, and resolving data quality issues.
• Investigate and process corporate actions, applying judgment on holdings and analytics.
• Monitor data alerts across cross-reference, market data, and characteristics pipelines.
• Build and maintain investment-ready data interfaces for liquidity, market cap, sector classifications, and fundamental ratios.
• Collaborate with data vendors (Bloomberg, FactSet, MSCI, and others) and understand dataset strengths and quirks.
• Validate and reconcile data across security master and identifiers (SEDOL, CUSIP, ISIN, FIGI).
• Partner with data engineers to define data behavior, quality checks, and monitoring thresholds.
• Work with researchers and portfolio managers to align data definitions with investment use cases.
• Develop data quality and reconciliation frameworks focused on investment impact.
• Contribute to the evolution of the data platform (Phoenix, Dagster, Rift) with metadata and modeling approaches.
• Identify recurring data issues and address root causes with engineering and vendors.

Skills

Python

SQL

Pandas

Dagster

Data quality

Data reconciliation

Security reference data

Corporate actions

Vendor data

Data pipelines

Education

Bachelor's degree in finance or related field

Tools

Dagster

Job description

• Own day-to-day investment data operations, including monitoring, triaging, and resolving data quality issues across security reference, pricing, corporate actions, and fundamentals
• Investigate and process corporate actions (e.g., mergers, spinoffs, splits, reclassifications), applying judgment to assess impact on holdings and analytics
• Monitor data alerts across cross-reference, market data, and characteristics pipelines, distinguishing true issues from benign anomalies
• Build and maintain investment-ready data interfaces for key metrics such as liquidity, issuer-level market cap, sector classifications, and fundamental ratios
• Work across major vendor data sources (Bloomberg, Capital IQ, Worldscope, FactSet, MSCI, CRSP, ICE, IBES, Russell), understanding their strengths, limitations, and quirks
• Validate and reconcile data across security master and identifier systems (SEDOL, CUSIP, ISIN, AcadianID), ensuring accurate linkage across securities, issuers, and time
• Partner with data engineers to define expected data behavior, contributing to data quality checks, transformation logic, and monitoring thresholds
• Collaborate with researchers and portfolio managers to align data definitions with real investment use cases
• Develop and refine data quality and reconciliation frameworks focused on investment impact, not just technical completeness
• Contribute to the evolution of the data platform (e.g., Phoenix, Dagster, Rift), including dataset definitions, metadata, and modeling approaches
• Identify recurring data issues and partner with engineering and vendors to address root causes

Qualifications

• Bachelor's degree in Finance, Economics, Mathematics, Computer Science, or a related field (or equivalent experience)
• Significant experience working with investment data in an institutional asset management or quantitative environment
• Deep familiarity with major financial data vendors and how their datasets are used in practice
• Strong understanding of security reference data and identifier systems (SEDOL, CUSIP, ISIN, FIGI), including corporate action impacts
• Hands-on experience with corporate actions and their downstream implications
• Proficiency in Python and SQL for data analysis and validation (experience with Pandas, Polars, Dagster, or similar tools preferred)
• Ability to reason about data at both the record and portfolio level, with a clear understanding of investment implications
• Experience building or contributing to data quality, monitoring, or reconciliation frameworks
• Working knowledge of systematic investment workflows (e.g., factor models, portfolio construction, execution)
• Strong cross-functional collaboration skills across engineering, research, and portfolio management teams
• Comfort operating in evolving data environments, balancing stability with modernization

  Our Commitment to Inclusion & Belonging

  The Hollister Group is an equal opportunity employer. We welcome and encourage applications from people who are under-represented in their respective occupations or positions.