Senior Quantitative Developer / Data Scientist - Enterprise Data Technology

• Posted 60+ days ago • Updated 8 hours ago

Full Time

Fitment

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Job Details

Skills

FOCUS
Decision-making
Core Data
Data Engineering
Statistical Models
Algorithms
Data Integrity
Data Validation
Quantitative Analysis
Data Science
Trading
Equity Derivatives
Management
Profit And Loss
Statistics
Mathematical Modeling
Data Quality
Equities
Reference Data
Pricing
Research
Workflow
Quantitative Research
Data Flow
Python
SQL
Time Series
Testing
Communication
Data Management
Fixed Income
FX
Derivatives
Meta-data Management

Summary

About the Team

Bam's Enterprise Data Technology team is responsible for building and maintaining Balyasny's core research and reference data platforms, with a heavy focus on building cross-asset data quality infrastructure. We are a central technology function that directly enables investment decision-making across the firm's strategies.

The Role

We are seeking a Senior Quantitative Developer / Data Scientist to design, build, and enhance mathematical models that validate, monitor, and improve the quality of our core data assets. This is a high-impact role at the intersection of quantitative research, data engineering, and platform development, ideal for someone who has operated in environments where data integrity directly influences trading and research outcomes.

What You'll Do

Develop and implement statistical models and algorithms to detect anomalies, validate data integrity, and expand coverage across asset classes (equities, futures, fixed income, FX, and more)
Build scalable, production-grade data quality frameworks that serve as the foundation for firm-wide research and trading systems
Partner with investment teams to understand data requirements and translate them into robust quality metrics and monitoring solutions
Continuously research and apply best practices in data validation, statistical testing, and quantitative analysis

What We're Looking For

Senior-level experience (typically 7+ years) in a quantitative development, data science, or research engineering capacity
Background in a commercial trading or research environment: ideally at a systematic fund, sell-side research desk (e.g., swaps, rates, or equity derivatives at a firm like JP Morgan), or similar organization where data-driven decisions have direct P&L impact
Strong foundation in statistics and mathematical modeling: you think like a statistician and can design rigorous tests for data quality and consistency
Experience with equities and/or futures data: including reference data, corporate actions, pricing, and related research workflows
Systematic or quantitative research experience: you understand how data flows into models and the downstream consequences of data errors
Proficiency in Python, SQL, and modern data infrastructure; familiarity with time-series analysis, hypothesis testing, and anomaly detection techniques
Excellent communication skills and the ability to work cross-functionally with technology and investment professionals

Nice to Have

Experience with cross-asset data platforms or enterprise data management
Exposure to fixed income, FX, or derivatives data
Familiarity with data observability, lineage, or metadata management tools

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10125634
Position Id: 70ee033aa1141b216949470804fa569b
Posted 30+ days ago

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