Senior Data Scientist at ICS GLOBALSOFT | Torre
Senior Data Scientist
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ICS GLOBALSOFT

Senior Data Scientist

ICS GLOBALSOFT
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Full-time

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Remote (for Mexico residents)
Posted 6 months ago

Responsibilities

Main Skills: - Convex optimization - CVXPY - Portfolio optimization - Capital allocation - Quantitative modeling - Financial modeling - Capital markets - Python - NumPy - pandas - SciPy - Excel - Risk metrics - Stress testing Summary: We are seeking a Senior Data Scientist with strong quantitative skills and hands-on experience building convex optimization models using CVXPY. This role will focus on developing portfolio construction, projection, and capital allocation models within a capital markets or institutional investing environment. The ideal candidate combines advanced Python proficiency, financial modeling expertise, and practical experience translating investment constraints into formal convex optimization problems. Core Responsibilities: - Formulate and implement convex optimization models using CVXPY for portfolio construction and capital allocation. - Develop projection frameworks to enforce portfolio constraints such as exposure limits, leverage, turnover, and risk budgets. - Integrate CVXPY-based optimization routines into scalable Python workflows. - Build and maintain financial models in Python and Excel. - Partner with investment stakeholders to translate requirements into mathematically sound models. - Validate models through stress testing, sensitivity analysis, and performance diagnostics. Required Experience: - Six or more years of experience as a Data Scientist, Quantitative Analyst, or similar role. - Demonstrated production experience using CVXPY for convex modeling and constrained optimization. - Strong proficiency in Python including NumPy, pandas, SciPy, and numerical solvers. - Solid financial modeling experience in Excel and Python. - Experience in capital markets, asset management, hedge funds, or institutional investing. - Working knowledge of portfolio optimization concepts and risk metrics. Education: - Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Finance, Engineering, or Computer Science. - Equivalent professional experience in quantitative finance or data science will be considered.
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