ERM Data Engineer / Scientist
- Collect, clean, and preprocess data from various sources.
- Analyze data to identify trends, patterns, and insights.
- Develop and implement predictive models and machine learning algorithms.
- Create data visualizations and dashboards to communicate findings to stakeholders.
- Collaborate with cross-functional teams to understand and solution for business needs and provide data-driven solutions.
- Stay up-to-date with the latest industry trends and technologies in data science.
- Ensure compliance and governance during data use, working with data governance teams to promote responsible data usage.
- Participate in the development of ERM data warehouses and data marts, collaborating with Data Architects and data engineers.
- Promote data and analytics capabilities to ERM risk dimension owners and educate them on optimized ways to leverage data intelligence to achieve risk and business goals.
- Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
- Adheres to Bank policies and procedures and completes required training.
- Identifies and reports suspicious activity.
- 5+ years proven experience as a Data Engineer / Scientist or in a similar role required.
- Strong knowledge of data engineering, statistical methods and machine learning algorithms required.
- Proficiency in programming languages such as Python, R, or SQL required.
- Experience with data visualization tools such as Tableau, Power BI, or similar required.
- Excellent problem-solving skills and attention to detail required.
- Strong communication skills and the ability to present complex data in a clear and concise manner preferred.
- Experience with AWS data tools.
- Agile / Scrum Master preferred.
- Amazon Web Services (AWS) Professional certification preferred.
- Experience with big data technologies such as Hadoop, Spark, or similar.
- Knowledge of AWS cloud platform.
- Familiarity with data warehousing and ETL processes.
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