Quant analyst

This role is for one of the Weekday's clients

Requirements

Key Responsibilities

• Assist in building, validating, and optimizing quantitative models for trading, pricing, forecasting, or risk management.
• Gather, clean, and analyze large structured and unstructured datasets from internal and external data sources.
• Apply statistical and machine learning techniques to identify patterns, generate insights, and develop predictive models.
• Implement data processing and analytical workflows using Python and associated scientific libraries (Pandas, NumPy, SciPy, Scikit-Learn, etc.).
• Support back-testing and scenario evaluation of algorithms and strategies to assess performance and robustness.
• Collaborate with technology and product teams to deploy models into production environments and enhance analytical frameworks.
• Prepare research reports, visualizations, and presentations to communicate findings and recommendations to stakeholders.
• Maintain thorough documentation of models, methodologies, datasets, and assumptions.
• Continuously monitor model performance, market trends, and technical developments to identify improvement opportunities.
  

Required Skills & Qualifications

• Bachelor's degree or higher in a relevant field such as Quantitative Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or related discipline.
• 0-2 years of experience in a quantitative analytics, research, data science, or financial modeling role (internships included).
• Strong proficiency in Python programming, including data manipulation and scientific computing libraries.
• Solid understanding of probability, statistics, linear algebra, and time series concepts.
• Strong problem-solving abilities and logical reasoning skills with attention to detail.
• Ability to work independently and collaboratively in a high-performance environment.
• Strong communication skills to present technical insights in an understandable manner.
  

Preferred/Good-to-Have Skills

• Exposure to machine learning algorithms and model evaluation practices.
• Familiarity with SQL, data visualization tools (e.g., Power BI, Tableau, Matplotlib, Plotly), or cloud platforms.
• Understanding of financial instruments, derivatives, capital markets, and trading concepts.
• Experience with back-testing frameworks or real-time analytics systems.
  

Who You Are

• Curious and passionate about using data to solve real-world problems.
• Self-driven with a willingness to learn continuously and explore new techniques.
• Comfortable working with ambiguity and delivering high-quality output under deadlines.
• Team-oriented with a positive attitude and ownership mindset