Senior Business Intelligence Analyst - Risk

What You’ll Be Doing

• Collect, clean, and preprocess large datasets to ensure data quality and reliability.
• Conduct exploratory data analysis to identify patterns, trends, and anomalies.
• Collaborate with risk-modeling, anti-fraud, policy, and other business stakeholders to deploy feature pipelines, and ETLs.

Statistical Analysis:

• Apply statistical methods to analyze data and extract meaningful insights for institutional clients.
• Develop and implement predictive models to support decision-making processes.
• Utilize programming languages such as Python,etc. for data manipulation, analysis, and visualization.
• Collaborate with cross-functional teams to integrate analytical solutions into business processes.

Business Intelligence:

• Interpret and communicate findings to non-technical stakeholders through reports, dashboards, and presentations.
• Collaborate with business units to understand analytical requirements and provide actionable recommendations.
• Monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure timelines are met with our internal stakeholders.
• Handling Ad-hoc analysis for risk related data request.
• Analyze new data sources and work with stakeholders to understand the impact of integrating new data into existing pipelines and models

• Bachelor's or Master's degree in a relevant field (e.g., Data Science, Statistics, Computer Science).
• Minimum of 5 years of hands-on experience in data analysis. Prior experience in crypto or traditional finance is preferred.
• Strong proficiency in Python programming languages is a must
• Proven track record of working with large datasets and performing complex analyses.
• Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses and action-oriented outcomes.
• Solid knowledge on data modelling (e.g. Random Forest model, Clustering, SVN and so on
• Strong attention to details and ability to notice discrepancies in data.
• Familiarity with business intelligence tools and data visualization techniques

Nice-To-Haves

• Experience with machine learning algorithms and techniques.
• Knowledge of database management and SQL.
• Ability to work independently and collaboratively in a fast-paced environment.
• Strong problem-solving skills and attention to detail.

• Competitive total compensation package
• L&D programs and Education subsidy for employees' growth and development
• Various team building programs and company events
• More that we love to tell you along the process!

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