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Unreal Gigs

Quantitative Analyst (The Data Strategist)

Unreal Gigs, San Francisco, California, United States, 94199


Are you passionate about leveraging data and advanced statistical models to drive impactful investment and business decisions? Do you excel in building and refining quantitative models that deliver insights and support financial strategies? If you’re ready to apply your quantitative skills to unlock data-driven opportunities,

our client

has the perfect role for you. We’re seeking a

Quantitative Analyst

(aka The Data Strategist) to develop models and analyses that guide investment strategies, risk management, and predictive analytics. As a Quantitative Analyst at

our client , you’ll collaborate with portfolio managers, data scientists, and financial analysts to design data models and algorithms that uncover insights from complex datasets. Your expertise will be vital in transforming data into strategic assets and driving key financial decisions. Key Responsibilities: Develop and Test Quantitative Models:

Design and build quantitative models for risk assessment, pricing, and investment strategies. You’ll validate models through rigorous backtesting and optimize them for accuracy and performance. Analyze Financial Markets and Data Patterns:

Conduct in-depth analyses of financial markets, identifying trends, correlations, and anomalies. You’ll provide insights that support trading strategies and portfolio optimization. Implement Statistical and Machine Learning Techniques:

Use advanced statistical methods and machine learning algorithms to analyze large datasets. You’ll apply techniques such as regression analysis, time-series forecasting, and clustering to extract valuable insights. Collaborate on Strategy Development:

Work closely with investment teams and risk managers to align quantitative models with strategic objectives. You’ll contribute to decision-making processes and advise on model-driven strategies. Monitor and Refine Models Over Time:

Track model performance and recalibrate as needed to adapt to market changes. You’ll implement feedback loops and monitor for model drift to ensure ongoing reliability. Automate Data Analysis and Reporting:

Develop scripts and workflows to automate data analysis and streamline reporting. You’ll use programming languages like Python or R to make quantitative processes more efficient. Stay Updated on Industry Trends and Regulatory Changes:

Keep current with market trends, regulatory developments, and advancements in quantitative finance. You’ll adapt models and strategies as needed to maintain compliance and optimize performance. Required Skills: Quantitative Modeling Expertise:

Strong knowledge of building and testing quantitative models, with expertise in statistical methods, time-series analysis, and financial modeling. Programming and Scripting:

Proficiency in Python, R, or MATLAB for data analysis, modeling, and automation. Familiarity with SQL for data extraction and manipulation is also essential. Financial Market Knowledge:

Understanding of financial markets, asset classes, and trading strategies. You can interpret economic indicators and their impact on market dynamics. Analytical and Problem-Solving Skills:

Proven ability to approach complex problems analytically and develop data-driven solutions. You’re capable of conducting in-depth research and analysis. Communication and Presentation:

Strong written and verbal communication skills to present findings and explain complex models to non-technical audiences. Educational Requirements: Bachelor’s or Master’s degree in Quantitative Finance, Economics, Statistics, Mathematics, or a related field.

Equivalent experience in quantitative analysis or finance may be considered. Certifications in quantitative finance or risk management (e.g., CFA, FRM, CQF) are advantageous. Experience Requirements: 3+ years of experience in quantitative analysis or data modeling,

with a proven track record of building impactful models. Experience working with large financial datasets and managing data from market data providers. Familiarity with risk management practices and regulatory frameworks in financial services is a plus.

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