Must have- Scala, Benchmarking, Security, Metadata, Machine Learning, Statistics, Analytics, Data Analysis , Target, Policies ,Services, Python ,Apache
Must have Financial Services industry domain exp
- Manage and ensure data quality, integrity, normalization, and accuracy of available datasets.
- Improve data quality as per the data quality framework and collaborate with data owners.
- Conduct internal and external benchmarking to identify factors influencing data quality.
- Design and manage the reporting environment, including data sources, security, and metadata.
- Generate business insights using BI dashboards to guide senior managers in decision-making.
- Support digitization initiatives to enhance the quality of data.
- Conduct root cause analysis using quality analysis tools, machine learning, and statistics.
- Assist organizations in making key decisions based on integrated analytics involving different datasets.
- Perform predictive data analysis, generate indications for focus areas, and proactively target improvements.
- Maintain and re-engineer existing ETL processes to increase data accuracy, stability, and pipeline performance.
- Apply advanced statistical techniques for complex data analysis.
- Interpret data and analyze results using statistical techniques, developing analytical reports.
- Adhere to compliance procedures in accordance with regulatory standards, requirements, and policies.
- Demonstrate sufficient business acumen to understand business objectives and dynamics.
Job Qualifications:
- Bachelor's or master's degree in Computer Science, Information Management, Statistics, or a related field.
- 10+ years of overall experience with a minimum of 5+ years in the Financial Services industry in an analytical role focused on querying data, analysis, and presentation.
- Proficient in Python, R Programming, Scala, Apache Spark, and AWS Redshift.
- Knowledge of analytics tools like Tableau, Power BI, Excel VBA Macros, RSPSS, SAS is an added advantage.
- Proven working experience as a data analyst or business data analyst.
- Experience in working with Business Intelligence tools/platforms and systems.
- Strong knowledge of data pre-processing and exploratory data analysis using various tools.
- Hands-on experience in Descriptive/Predictive/Prescriptive Analytical techniques.
- Ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.