Financial Analyst (Stock & Crypto Investment)

As a Financial Analyst in investment product development, you will support the creation of innovative, user-focused investment offerings, while ensuring accurate and reliable financial data. Your work will involve analyzing market trends, developing financial models for asset selection and portfolio strategies, troubleshooting data discrepancies, and refining algorithms to enhance the performance of our investment products. Your contributions will play a vital role in shaping high-quality investment products that seamlessly align with market trends and user expectations.

What will you do:

• Conduct financial analyses to ensure data accuracy and provide insights that drive the development of innovative investment products.

• Evaluate market trends and key performance indicators to inform asset selection and optimize portfolio strategies.

• Build and refine financial models to enhance product features, focusing on asset weighting, rebalancing, and performance forecasting.

• Identify and resolve discrepancies in financial data, maintaining the integrity and reliability of platform information.

• Develop and fine-tune algorithms to improve investment product performance and the overall user experience.

• Collaborate with cross-functional teams to ensure alignment between product features and market demands, as well as user behavior.

What we are looking for:

• Bachelor’s degree in Finance, Economics, or related field, CFA is a plus.

• Minimum 3 years of experience in financial analysis or investment product development, preferably with exposure to stocks (e.g., securities or mutual funds).

• Personal experience in crypto and/or US stocks investments is a plus.

• Strong skills in financial modeling and portfolio optimization.

• Proficient in Excel, SQL, and financial analysis tools.

• Ability to analyze market trends.

• Experience developing algorithms to enhance investment product performance.

• Attention to detail with the ability to identify and resolve data discrepancies.

• Strong collaboration skills and experience working across teams.

• Excellent communication skills for presenting insights and recommendations.