Data Analytics

This role is ideal for someone with strong expertise in SQL, Python, Hadoop/Oracle and Pyspark, and a solid background in data analysis and wrangling.

You will play a key role in building and maintaining analytical solutions that drive insights, especially in the area of fraud detection within card transactions and account opening domains.

Key Responsibilities:

• Develop, maintain, and optimize complex SQL queries to support data extraction and transformation activities.
• Utilize Python for advanced data processing, automation, and analytical modeling.
• Build and maintain Tableau dashboards that provide actionable insights to stakeholders.
• Perform data wrangling and cleansing from various sources to prepare data for analysis.
• Conduct detailed data analysis to uncover trends, patterns, and potential fraudulent activity.
• Collaborate with fraud analytics and operations teams to develop and enhance fraud detection frameworks.
• Document data processes and maintain data integrity across workflows.
• Contribute to continuous improvement in data pipelines, tools, and reporting mechanisms.

Required Skills and Qualifications:

• Proven experience in writing efficient and complex SQL queries for large datasets.
• Strong programming skills in Python, with knowledge of data libraries such as Pandas, NumPy, etc.
• Hands-on experience building visualizations and dashboards using Tableau.
• Experience with data wrangling, cleaning, and transformation techniques.
• Solid understanding of data analysis methodologies and problem-solving using data.
• Excellent communication skills and ability to present technical findings to non-technical stakeholders.
• Attention to detail and commitment to delivering high-quality work.