AddressManager - Data Analytics
Manager - Analytics (Data Analytics)
- Consulting Background, ie, Analytics firm experience preferred (Payments Industry and Retail background preferred for General Analytics and Retail Analytics respectively).
- Hands on SQL Mandate with any Visualization experience ; Tableau preferred + priority.
- For Analytics Role, kindly don't get profiles from IT domain with DW or any data engineering profiles. Strictly looking only from Analytics domain.
- Experience in Data Analytics, Dashboards, BI tools, Data Crunching, Reporting, Data Modeling, Insights Generation etc.
- Knowledge on advanced analytics or ML modeling will be an added advantage.
- IIT/IIM folks preferred
- For Banking domain , client management and team leading experience is mandatory.
Role & Responsibilities :
- Interact with the client to understand their requirements and communicate / brainstorm solutions
- Contribute to how analytical approach is structured for specification of analysis
- Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems
- Participate in design of analysis and modeling approach with managers and modelers
- Extremely comfortable working with data, including managing large number of data sources, analyzing data quality, and pro-actively working with client's data/ IT teams to resolve issues
- Use variety of analytical tools (SQL, Python, Tableau/Power BI) for insight generation & enabling the client with data driven decision making
- Reformulate highly technical information into concise, understandable terms for presentations
Candidate Profile :
- Master's or Bachelor's degree in math, statistics, economics, computer engineering or analytics related field from top-tier universities with strong record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work
- Analytics delivery experience preferably in retail/media/sports/payments/Banking Domain
- Very strong analytical skills with the demonstrated ability to research and make decisions based on the day-to-day and complex customer problems required
- Hands-on experience using one or more analytics tools such as Python/ R/SQL & Big data tools & platforms such as Hive, Spark, Tez, HDFS is mandatory
- Good knowledge of visualization tools such as Power BI & Tableau is preferred
