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Senior Quant Developer

LinkedIn Man Group Boston, MA
Mid-Senior level Posted April 5, 2026 Job link
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Requirements
  • 5-7 years of professional experience in software engineering, preferably with a focus on quantitative applications
  • Expert knowledge of Python and Pandas and proficiency with related scientific libraries including NumPy, SciPy, statsmodels, and scikit-learn
  • Experience developing mission-critical production systems, with knowledge of best practices for testing, monitoring, and deployment
  • Proficient on Linux platforms and strong understanding of Git
  • Working knowledge of one or more relevant database technologies, such as MS SQL, Postgres, or MongoDB
  • Demonstrated experience working with large data sets, both structured and unstructured
Preferred Skills
  • Advantageous
  • Experience in quantitative software development within a front-office setting, such as at a hedge fund, proprietary trading firm, or investment bank
  • Experience mentoring junior team members and managing projects
  • Experience building web applications using modern frameworks like React
  • Proficient with distributed computing technologies such as Spark, Dask, Kubernetes, Redis
  • Knowledge of modern data engineering practices including data pipeline & ETL tools, distributed storage & processing and data warehousing
  • Strong understanding of financial markets and instruments
  • Experience working with financial market data
  • Relevant mathematical knowledge e.g., statistics, time-series analysis
  • Strong interpersonal skills: able to establish and maintain a close working relationship with quantitative researchers, portfolio managers, traders and senior business people alike
  • Confident communicator: able to argue a point concisely and deal positively with conflicting views
Education
  • (Not required) – 5-7 years of professional experience in software engineering, preferably with a focus on quantitative applications
  • (Not required) – Strong academic record and a degree with high mathematical and computing content e.g., Computer Science, Mathematics, Engineering or Physics