Balyasny Asset Management L.P.
Data Analyst - L/S Equity
Balyasny Asset Management L.P.United States3 days ago
Full-timeAnalyst

Description Summary

Balyasny Asset Management (BAM) is a global, multi-strategy investment firm with $32 billion in assets under management. We are looking for a Data Analyst to work on a L/S Equity Portfolio Manager team in New York on projects related to data analysis, data-driven idea generation and fundamental research.


RESPONSIBILITIES

  • Collaborate with Portfolio Manager and team to brainstorm creative uses for data in the investment process
  • Identify, ingest, and analyze cutting-edge alternative datasets – including cleaning, organizing, tagging, indexing, etc.
  • Conduct independent research on various new datasets and influence actual trading strategies
  • Pinpoint trends, correlations, and patterns in complicated data sets to provide custom solutions to management
  • Identify and analyze relevant industry metrics, business rational
  • Evaluate new coverage opportunities across Consumer, TMT, and/or Industrials sectors
  • Building and maintaining detailed models from scratch
  • Design, build and maintain data products that enable you to analyze key performance indicators (KPIs)


QUALIFICATIONS & REQUIREMENTS

  • Bachelors/Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or a related field
  • 2+ years of experience in a data driven or quantitative role
  • Strong analytical and data processing skills (Python/SQL)
  • Proficient with data ETL (e.g. Airflow, creating and updating databases) and analysis (familiar with libraries like Pandas, NumPy etc.)
  • Experience with large datasets a plus
  • Experience with cloud architecture (e.g. AWS, Snowflake etc.)
  • Knowledge of data visualization tools
  • Self-starter, results-driven attitude with great attention to detail, ability to multitask and think outside of the box
  • Ability to explain technical concepts (programming/databases/stats) to less technical audiences

Key Skills

Ranked by relevance