We are seeking a skilled System Analyst with 3-5 years of experience in Risk Data Science to join our team.
The ideal candidate will have a strong foundation in Hadoop , SQL Server 2012 , and data analytics, with a focus on building and maintaining scalable data solutions to assess and mitigate risks.
You will collaborate with data scientists, risk analysts, and IT teams to design data-driven risk management solutions.
Key Responsibilities: Analyze and interpret complex data sets related to risk factors, ensuring accurate risk assessment and data integrity.
Design, implement, and maintain risk data models using Hadoop ecosystems, including HDFS, MapReduce, Hive, and Pig.
Develop, manage, and optimize databases, data warehouses, and ETL processes on SQL Server 2012 to support risk data analytics.
Collaborate with data science and business teams to integrate data-driven insights into risk management strategies.
Perform data cleansing, data mining, and statistical analysis to support decision-making in risk mitigation.
Create and automate reports and dashboards for key risk metrics, leveraging SQL , Hadoop , and data visualization tools.
Monitor and maintain data pipelines, ensuring seamless data integration and availability for risk assessment purposes.
Troubleshoot and resolve performance issues in data systems and risk analytics platforms.
Document technical processes, workflows, and data transformation methodologies to ensure traceability and transparency in data management.
Required Qualifications: Bachelors degree in Computer Science, Information Technology, Data Science, or a related field.
3-5 years of experience working in data analysis, system analysis, or risk management in a data-driven environment.
Proficiency in Hadoop ecosystem tools (HDFS, MapReduce, Hive, Pig, Spark) and experience in managing large data sets.
Strong expertise in SQL Server 2012 , including database design, query optimization, and ETL process development.
Proven ability to analyze, model, and interpret complex datasets to generate actionable risk insights.
Strong knowledge of data governance, data quality, and risk management principles.
Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
Preferred Qualifications: Experience with risk modeling or quantitative analysis in financial services, insurance, or a related industry.
Knowledge of scripting languages like Python or R for data analysis.
Familiarity with big data tools like Spark , Kafka , or Cloudera .
Experience with data visualization tools (Tableau, Power BI, etc.)
for risk reporting.