System Analyst -Data Science

About the job System Analyst -Data Science

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.