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PRIMARY FUNCTIONS
- Utilize tools like SQL/Python to retrieve data from primary and secondary sources, including databases, credit reports, and other external sources
- Establish clear criteria for clean and usable data that aligns with business, considering data meaning and expected behavior
- Employ data cleaning techniques to identify and rectify inconsistencies, missing values, duplicates, and formatting errors within datasets
- Develop Python scripts to automate data extraction, preparation, and cleaning tasks, ensuring ongoing data quality and efficiency
- Leverage statistical tools to identify patterns, trends, and anomalies within complex datasets
- Assist in preparing comprehensive reports and interactive dashboards for stakeholders, effectively presenting trends, patterns, predictions, and other valuable insights derived from data analysis
- Clearly outline the methodology used, including the specific steps taken and the rationale behind them
- Actively immerse in relevant areas of the business and work with stakeholders to identify and process, and interpret data that can answer business questions and help identify opportunities
- Analyze local, national, and global trends that impact both the organization and the industry
- Provide support in maintaining the data models, infrastructure and processes to monitor and maintain data quality
EXPERIENCE:
- At least 5 years of data experience and a minimum of 3 years in data analysis
- Experience in data entry and cleaning, quality control, model validation, regression analysis, data visualization, and reporting tools
- High proficiency in SQL and Python is a must-have
- Preferred but not required experience in developing and maintaining data pipelines, data models and databases
- Experience in working with consumer loans/personal loans is a must
- Preferably with previous startup experience
PRIMARY FUNCTIONS
- Utilize tools like SQL/Python to retrieve data from primary and secondary sources, including databases, credit reports, and other external sources
- Establish clear criteria for clean and usable data that aligns with business, considering data meaning and expected behavior
- Employ data cleaning techniques to identify and rectify inconsistencies, missing values, duplicates, and formatting errors within datasets
- Develop Python scripts to automate data extraction, preparation, and cleaning tasks, ensuring ongoing data quality and efficiency
- Leverage statistical tools to identify patterns, trends, and anomalies within complex datasets
- Assist in preparing comprehensive reports and interactive dashboards for stakeholders, effectively presenting trends, patterns, predictions, and other valuable insights derived from data analysis
- Clearly outline the methodology used, including the specific steps taken and the rationale behind them
- Actively immerse in relevant areas of the business and work with stakeholders to identify and process, and interpret data that can answer business questions and help identify opportunities
- Analyze local, national, and global trends that impact both the organization and the industry
- Provide support in maintaining the data models, infrastructure and processes to monitor and maintain data quality
EXPERIENCE:
- At least 5 years of data experience and a minimum of 3 years in data analysis
- Experience in data entry and cleaning, quality control, model validation, regression analysis, data visualization, and reporting tools
- High proficiency in SQL and Python is a must-have
- Preferred but not required experience in developing and maintaining data pipelines, data models and databases
- Experience in working with consumer loans/personal loans is a must
- Preferably with previous startup experience