- Provide innovative analytical insights within the Data Products Program
- Conduct detailed data analysis on data used across business units to evaluate business processes
- and improve on/create new features
- Respond to data and product related inquiries in real time to support business and technical
- teams
- Perform various data analytics in SQL and MS Excel using statistical models or industry accepted
- tools
- Provide relational database expertise to construct and execute SQL queries to be used in data
- analysis activities
- Provide data solutions, tools, and capabilities to enable self-service frameworks for data
- consumers
- Provide expertise and translate the business needs to design; and develop tools, techniques, and
- metrics, and dashboards for insights and data visualization
- Responsible for developing and executing tools to monitor and report on data quality
- Responsible for establishing appreciation and adherence to the principles of data quality
- management, including metadata, lineage, and business definitions
- Provide support to Tech teams in managing security mechanisms and data access governance.
Requirements
- A high level of mathematical ability.
- The ability to analyze, model and interpret data.
- Problem-solving skills.
- A methodical and logical approach.
- The ability to plan work and meet deadlines.
- Accuracy and attention to detail.
- Interpersonal skills.
- Team work skills.
- Written and verbal communication skills.
Education:
Employers often prefer data analysts with a Master s degree in Analytics, Computer Science, or Data Science; Mathematics or in a related field and 3-5 years of industry experience in data analysis using SQL
Certifications: CIPM, CFA, and/or CAIA certification(s) with proven track record of relevant technical experience; SQL and relational database knowledge are required for the senior data analyst position in the financial sector
Knowledge: The senior data analyst position is an advanced data management role that requires extensive experience. Employers often look out for at least 7-10 years of industry experience as a Business/Data Analyst with 3-5 experience in data analysis using tools such as SQL and Excel
Employers also seek applicants with competence in the following areas: Understanding of Scripting experience in (Python, Perl, JavaScript, Shell); Practical knowledge of data in various forms (data warehouses/SQL, unstructured data environments/PIG,HIVE, Impala); Familiarity with BI reporting tools (i.e. Tableau and Business Objects); Experience working within process management and improvement methodologies Lean, Six Sigma, etc. and demonstrating knowledge of data governance, data quality management concepts and data quality tools (i.e. Informatica DQ); Understanding of Agile development methodologies, software design patterns, network design and architecture; Experience in quantitative analysis and statistical modelling
A high level of mathematical ability. The ability to analyze, model and interpret data. Problem-solving skills. A methodical and logical approach. The ability to plan work and meet deadlines. Accuracy and attention to detail. Interpersonal skills. Team work skills. Written and verbal communication skills. Education: Employers often prefer data analysts with a Master s degree in Analytics, Computer Science, or Data Science; Mathematics or in a related field and 3-5 years of industry experience in data analysis using SQL Certifications: CIPM, CFA, and/or CAIA certification(s) with proven track record of relevant technical experience; SQL and relational database knowledge are required for the senior data analyst position in the financial sector Knowledge: The senior data analyst position is an advanced data management role that requires extensive experience. Employers often look out for at least 7-10 years of industry experience as a Business/Data Analyst with 3-5 experience in data analysis using tools such as SQL and Excel Employers also seek applicants with competence in the following areas: Understanding of Scripting experience in (Python, Perl, JavaScript, Shell); Practical knowledge of data in various forms (data warehouses/SQL, unstructured data environments/PIG,HIVE, Impala); Familiarity with BI reporting tools (i.e. Tableau and Business Objects); Experience working within process management and improvement methodologies Lean, Six Sigma, etc. and demonstrating knowledge of data governance, data quality management concepts and data quality tools (i.e. Informatica DQ); Understanding of Agile development methodologies, software design patterns, network design and architecture; Experience in quantitative analysis and statistical modelling