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Salary
$200k – $300k per year
Location
In office (New York)
Seniority
Middle · 3+ years exp
Overview
Company
Impact
Profile match
Point72 is a global, multi-strategy hedge fund manager founded by Steven A. Cohen that invests across discretionary long/short equity, systematic, and macro strategies. The firm relies heavily on fundamental research, quantitative models, and advanced data analytics to allocate capital across international financial markets. Headquartered in Stamford, Connecticut, it also manages Point72 Ventures, an early-stage venture capital arm focused on investing in emerging technology startups.

A Career with Point72’s Market Intelligence Team

On our proprietary research team-Market Intelligence-you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products. We look for other bright, motivated, and collaborative people to join our team and grow with us-a majority of the leaders in our group were promoted from within.

What you’ll do

As a Data Engineer, you will help leverage knowledge graphs that connect companies, industries, and insights about the broader economy. This role begins as an individual contributor position with clear paths to expand your technical leadership as the platform grows. Specifically, you will:

  • Design and implement a comprehensive financial knowledge graph architecture with sophisticated data models that capture complex financial relationships.
  • Create robust graph processing pipelines for data ingestion, transformation, knowledge extraction, and advanced analytics capabilities.
  • Define and implement best practices for knowledge graph development, implementation, and maintenance across the organization.
  • Champion the adoption of graph-based solutions across Market Intelligence.

What excites you

  • You are passionate about designing data models that represent sophisticated financial relationships and dependencies. You find satisfaction in transforming disparate data sources into a unified, interconnected knowledge graph and implementing graph algorithms to uncover hidden patterns and relationships in financial data.
  • You excel at navigating organizational change management and driving adoption of new technologies across diverse teams. You are energized by working with stakeholders and productive collaboration that advances technical initiatives.
  • You are motivated by fast-paced environments that require adaptability and strategic problem-solving skills.
  • You are driven by creating graph-based solutions that help enhance investment decision-making processes.

What excites us

  • We value your proven ability to build and lead engineering teams through complex technical implementations. Your strong track record of hiring and developing technical talent in specialized domains will be essential as we grow our knowledge graph capabilities.
  • We are looking for deep expertise in graph data modeling and ontology design specifically for financial applications. Your hands-on experience with graph databases (Neo4j, TigerGraph, Amazon Neptune, etc.) and strong coding skills focused on developing graph-based applications and algorithms will drive our technical success.
  • We value interpersonal skills and a willingness to collaborate with stakeholders to achieve technical and business objectives.
  • We appreciate your demonstrated success in mentoring engineers and helping them grow into graph specialists.
  • We seek candidates with a methodical approach to solving complex data modeling and integration challenges. We value people who "elevate the room" through their work ethic, curiosity, and solution-oriented attitude, inspiring those around them to achieve more.

What’s required

  • 3+ years of experience in knowledge graph engineering, graph database development, or related work.
  • Proven experience leading technical teams and mentoring engineers to develop technical talent.
  • Strong expertise in graph data modeling, ontology design, and semantic technologies.
  • Hands-on experience with at least one major graph database technology.
  • Advanced programming skills in Python or another high-level language.
  • Experience with data integration from diverse sources into unified knowledge graphs.
  • Track record of successfully implementing change management for technical initiatives.
  • Demonstrated ability to work effectively with challenging stakeholders.
  • Experience hiring and building specialized technical teams.
  • Commitment to the highest ethical standards.

We take care of our people

We invest in our people, their careers, their health, and their well-being. When you work here, we provide:

  • Fully-paid health care benefits
  • Generous parental and family leave policies
  • Volunteer opportunities
  • Support for employee-led affinity groups representing women, people of color and the LGBT+ community
  • Mental and physical wellness programs
  • Tuition assistance
  • A 401(k) savings program with an employer match and more

About Point72

Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit  https://point72.com/.

The annual base salary range for this role is $200,000-$300,000, which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.  

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