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Job Summary
Key Responsibilities:Data Exploration & Management:
Collect, clean, and prepare structured and unstructured financial data (e.g., client transactions, market prices, investment flows). Assist in preparing, cleansing, and transforming data for the BI environment, ensuring data quality and consistency.
Model Development:
Support the development of machine learning models.
Help evaluate model performance, document outputs, and improve feature engineering.
Implement anomaly detection models across business units.
Reporting & Visualization:
Create reports (Power BI) to communicate findings to stakeholders.
Collaboration:
Work closely with different teams to understand their data needs and provide data-driven insights.
Partner with data engineers, analysts, and business stakeholders to ensure analytical outputs are relevant and actionable. Contribute to internal automation, reconciliation, and alerting tools to streamline operations.
Continuous Improvement:
Identify and propose process improvements and efficiencies.
Stay updated with the latest industry trends, tools, and best practices in data analysis.
Qualifications & Skills:
Education:
Bachelor’s degree in data science, Statistics, Finance, Economics, Computer Science, or related field.
Advanced degree or certification in data analysis or finance is a plus.
Experience:
Minimum of 0-2 years of experience in data analysis within the finance industry.
Technical Skills:
Proficient in Python (pandas, matplotlib, scikit-learn).
Familiarity with Power BI, Excel, and reporting tools.
Comfortable writing basic SQL queries.
Familiarity with financial databases and platforms.
Understanding data pipelines, version control (Git), and cloud environments is a plus.
Analytical Skills:
Strong analytical and critical thinking skills with keen attention to detail.
Ability to interpret complex data and present it in an understandable format.
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