Junior Quantitative Analyst

We are seeking a detail-oriented and analytical Junior Quantitative Analyst to support data-driven decision-making through statistical analysis, mathematical modeling, and quantitative research. The successful candidate will work with experienced analysts and cross-functional teams to collect, process, and interpret complex datasets, identify trends, and develop analytical solutions that support business objectives.

This is an excellent opportunity for an early-career professional with a strong foundation in mathematics, statistics, programming, and problem-solving to develop practical quantitative analysis skills.

• Data Analysis: Collect, clean, validate, and analyze datasets to identify patterns, trends, and meaningful insights.
• Quantitative Modeling: Assist in developing and testing statistical models, forecasting methods, and quantitative algorithms.
• Statistical Research: Apply statistical techniques and mathematical methods to evaluate business performance and support research initiatives.
• Programming and Automation: Use Python, R, SQL, or similar tools to process data, automate analytical tasks, and improve reporting efficiency.
• Model Testing: Evaluate model performance, investigate discrepancies, and document assumptions, limitations, and results.
• Reporting and Visualization: Prepare analytical reports, charts, dashboards, and presentations to communicate findings clearly.
• Collaboration: Work with senior analysts, data scientists, finance professionals, and other stakeholders to address analytical challenges.
• Documentation: Maintain accurate records of methodologies, data sources, calculations, and analytical procedures.

• Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, Finance, Engineering, or a related quantitative discipline.
• Strong understanding of probability, statistics, linear algebra, and basic mathematical modeling.
• Familiarity with Python or R for data analysis and statistical computing.
• Basic knowledge of SQL, databases, and data manipulation techniques.
• Experience with Excel and data visualization tools is an advantage.
• Strong analytical thinking, attention to detail, and problem-solving abilities.
• Ability to interpret numerical information and communicate findings effectively.
• Willingness to learn new analytical techniques, tools, and technologies.
• Previous internship, academic research, or project experience in quantitative analysis is desirable but not essential.

• Familiarity with regression analysis, time-series analysis, and forecasting.
• Basic understanding of financial markets, risk analysis, or optimization techniques.
• Exposure to machine learning concepts and model validation.
• Experience working with large datasets or statistical software packages.
• Ability to manage multiple analytical tasks and meet project deadlines.

• Competitive annual compensation based on qualifications and experience.
• Opportunities for professional development, training, and mentorship.
• Exposure to real-world quantitative research and analytical projects.
• A collaborative environment that encourages innovation and continuous learning.
• Opportunities to develop technical, statistical, and business analysis skills.
• Potential career progression into Quantitative Analyst, Data Scientist, Risk Analyst, or related positions.

Equal Opportunity Statement: We are committed to providing equal employment opportunities to all qualified applicants. Employment decisions are made without discrimination and in accordance with applicable laws.