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21Open Positions

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Fundamental Equities Data Analyst

Point72
Found 1 month ago
Location
Paris, France
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Not disclosed
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • Bachelor

Skills & Qualifications

Technical Skills

  • Python
  • R

Soft Skills

  • Team player
  • entrepreneurial spirit
  • good communication skills
  • Deep intellectual curiosity
  • lifelong-learning mindset
  • Commitment to the highest ethical standards

Job Description

As a hybrid data analyst/data engineer embedded in an investing team, you will help drive innovation by leveraging a variety of data sources and systems. You will work directly with a Portfolio Manager and their team of research analysts to connect data and fundamental research. Your work will support investment theses and help inform investment decisions. This role will start on a 6-month contract with the opportunity to renew. Specifically, you will: * Help analyze a broad universe of Compliance-approved data to directly influence idea generation and investment decisions, with an emphasis on equities. * Design, build, and maintain data products and predictive models that enable analysis of key performance indicators (KPIs) and forward-looking metrics relevant to your specific sector. * Build technologies to bolster research and trading efficiency. * Develop agile, automated systems that rapidly ingest, synthesize, and analyze diverse sets of information in real-time, producing actionable insights to support timely decision-making. * Automate and scale existing data infrastructure to enhance performance, reliability, and adaptability in handling complex, high-volume data streams. * Investigate and explore innovative approaches to extract meaningful information from complex datasets. * Stay on top of the newest technologies approved for use across the firm. * Partner with Compliance on various initiatives such as approved data sources, permissibility of systems, and analytics.

Requirements

  • Undergraduate degree or higher in a relevant field.
  • Experience working with diverse data types including structured, unstructured (e.g., text), and time-series data.
  • An interest in applying statistical concepts and large-scale data analysis to financial datasets.
  • Strong coding skills in a high-level programming language (e.g., Python, R, or similar).
  • Strong data visualization skills, with experience in creating informative visualizations.
  • Team player with an entrepreneurial spirit and good communication skills.
  • Deep intellectual curiosity and lifelong-learning mindset.
  • Commitment to the highest ethical standards.

Related Field

  • Data & Analytics

Related Subfield

  • Data Analysis
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