Business Intel Engineer, Amazon Pay
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Amazon's vision is to be the earths most customer centric company . The ambition of the Amazon payments business is to transform payments in India . The payments data team provides data and insights to the partner verticals so as to enable them to take decisions. This a senior role. The role requires team-work and building a business perspective. The individual will have to interact extensively with other members within the team, across business lines work in partnership with Machine Learning and Central Customer Analytic teams. There will be a steep learning curve, adding a fair amount of business skills to the individual.
Role Expectations
- Ability to do exploratory analysis: Fetch data from systems and analyze trends
- Identify consumer segments that need to be actioned to drive adoption of Amazon Pay
- Developing India specific customer segmentation models to improve the efficiency of marketing and financing product roadmap inputs .
- Establishing mechanisms for cross functional teams to consume customer insights to improve engagement along the customer life cycle
- Work with cross functional teams
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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Job ID: 153241453
Skills:
Nosql, Data Modeling, Quicksight, Tableau, Data Warehousing, Oracle, Redshift, Sql, Python, Etl
Skills:
Data Modeling, Data mining, Python, Sql, AWS technologies, ETL pipelines
Skills:
Nosql, Quicksight, Data Visualization, Data Warehousing, Tableau, Oracle, Redshift, Python, Sql, Etl
Skills:
Etl, Sql, Microsoft Excel, Oracle, Python, Nosql, Quicksight, Tableau, Data Modeling, Redshift
