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Fundamental Data Researcher

Point72 Asset Management - Chicago, New York

Posted Aug 15, 2024

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Data From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Application

Cover letter
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Assessment
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Deadline
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Where they hire

State eligibility is not yet verified.

About this role

Fundamental Data Researcher Chicago, New York ROLE A Cubist portfolio management team specializing in the systematic trading of US credit markets is looking for a highly talented Data Researcher. RESPONSIBILITIES - Design and own a process of normalizing and sanitizing fundamental data across a wide universe of public companies (based on 10Q, 10K, etc.) - Design and own a process of tracking real-time data of corporate bond issuances/redemptions/etc. and other relevant corporate events - Conduct independent research of the fundamental data, detecting anomalies and outliers. Prioritize and conduct deep dive case studies - In collaboration with the research team, make predictions of capital structure changes and corporate event outcomes - Proactively search for alternative, unstructured data sets with signal potential for corporate credit REQUIREMENTS - Undergraduate degree or higher in Accounting, Economics, Business, or other related discipline - 2+ years of work experience as an accountant, financial data analyst, industry analyst, or other related role - CPA or CFA is a plus. Coursework in Statistics and Econometrics and skills in empirical data analysis are a plus - Some programming skills are a plus (e.g., Python) and a strong self-learner - Tenacious, detail-orientated, and organized - Strong communication skills - Team player, driven and collaborative

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