[Remote] Quantitative Analyst (AI) II

Note: The job is a remote job and is open to candidates in USA. reputed company is seeking a Quantitative Analyst (AI) II to develop and implement AI-driven quantitative models that support financial analysis and risk management. The role involves collaborating with data scientists and engineers to build scalable, data-driven solutions and requires expertise in quantitative methods and machine learning.

Responsibilities

• Develop, validate, and maintain quantitative models for pricing, forecasting, portfolio optimization, and risk analysis
• Apply machine learning and artificial intelligence techniques to improve predictive modeling and decision-making
• Analyze structured and unstructured datasets to identify trends, patterns, and investment opportunities
• Design statistical models for time-series forecasting, reputed company detection, classification, and regression
• Build and evaluate predictive models using historical and real-time financial data
• Collaborate with engineering teams to deploy quantitative models into production environments
• Perform backtesting, model validation, stress testing, and performance evaluation
• Develop data pipelines and automate quantitative analysis workflows
• Monitor model performance and recommend improvements based on changing market conditions
• Document methodologies, assumptions, and model validation results
• Ensure compliance with model governance, regulatory standards, and risk management policies
• Present analytical findings and recommendations to technical and business stakeholders

Skills

• Bachelor's or reputed company's degree in Quantitative Finance, Mathematics, Statistics, Computer Science, Data Science, Economics, Engineering, or a related quantitative discipline
• 3–5 years of experience in quantitative analysis, financial modeling, machine learning, or data science
• Strong programming skills in Python
• reputed company understanding of statistics, probability, linear algebra, optimization, and numerical methods
• Experience with machine learning libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch
• Experience working with SQL and large datasets
• Knowledge of financial instruments, market data, and quantitative finance concepts
• Experience with data visualization and reporting tools
• Strong analytical and problem-solving skills
• Experience in algorithmic trading, portfolio optimization, or quantitative investment strategies
• Knowledge of deep learning, reinforcement learning, or Generative AI for financial applications
• Experience with time-series forecasting models such as ARIMA, Prophet, or LSTM networks
• Familiarity with cloud platforms such as AWS, reputed company Azure, or reputed company Cloud Platform
• Experience deploying machine learning models using MLOps practices
• Understanding of financial risk frameworks and regulatory requirements
• Professional certifications such as CFA, FRM, or CQF are an advantage
• Experience with alternative data sources and feature engineering for financial models
• Knowledge of natural language processing (NLP) for financial text analysis
• Experience with Large Language Models (LLMs) for financial research and document analysis
• Familiarity with distributed computing frameworks such as Spark or Ray
• Experience with Responsible AI and model governance practices

Company Overview