Quant analyst at Weekday AI

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python Programming, Statistical Techniques, Machine Learning, Data Analysis, Quantitative Modeling, Financial Markets, Problem Solving, Communication Skills, Data Visualization, SQL, Time Series Analysis, Attention to Detail, Team Collaboration, Research Skills, Model Validation, Data Processing, Documentation

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 0 years Location: Gurugram JobType: full-time We are seeking a highly motivated and analytical Quantitative Analyst to join our growing team. This role is ideal for recent graduates or early-career professionals with a strong passion for data-driven decision-making, financial markets, and quantitative modeling. As a Quant Analyst, you will work closely with senior analysts, product teams, and technology stakeholders to develop models, analyze datasets, support research initiatives, and contribute to strategic investment or risk decisions. The ideal candidate is detail-oriented, intellectually curious, and eager to continuously learn new concepts in quantitative finance and applied statistics. 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.

Responsibilities

The Quant Analyst will assist in building, validating, and optimizing quantitative models for various applications such as trading and risk management. They will also gather and analyze large datasets, apply statistical techniques, and collaborate with teams to deploy models into production.