Business Systems Analyst
The Business Systems Analyst will be a thought leader capable of asking the right business questions while bridging the gap between data, analytics, and business intelligence. The ideal candidate is expected to communicate effectively with executives and peers from the various departments to ensure efficient solutions that bring maximum value.
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- The Business Systems Analyst will be responsible for designing and implementing processes and layouts for complex, large-scale data sets used for modeling, data mining, and research purposes.
- Uncover business pain points and optimize data input from a wide range of enterprise business lines
- Design and build large and complex data sets, from spurious sources while thinking strategically about uses of data and how data use interacts with data design. Design and implement statistical data quality procedures for new data sources.
- Ability to communicate findings to business leaders in a way that can influence how an organization approaches a business challenge
- Develop algorithms/software for accessing and handling data appropriately. Implement and hand off data checking and updating procedures to teams.
- Visualize and report data findings creatively in a variety of visual formats that appropriately provides insights to the organization.
- Train others on what data is available and how to use various sources
- Source and data elements identification, data profiling, root cause analysis, issue management and documentation.
- Conduct and document data lineage from source to target, including data flows
- Conduct and document data mapping activities
- Implement data quality controls
- Ensure requirements are clearly, accurately and thoroughly documented and understood
Requirements:
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- Work with structured and unstructured data sets;
- Lead analytics projects to drive change and innovation in our build program.
- Perform hypothesis testing and develop predictive model;
- Evaluate and provide input on potential business intelligence solutions.
- Ability to apply statistical principles to data analytics;
- Comfortable in statistical analysis, clustering and data mining techniques to identify trends and insights
- Thorough understanding of relational database design;
- Highly proficiency in SQL, Python, Informatica, Hive QL.
- Familiar with machine learning, artificial intelligence and data mining algorithms
- Use of Enterprise Data Lake Architecture
Nice to have:
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- Experience in Banking/AML