Shazib M.
Business Intelligence
Shazib is a seasoned professional with 8 years of experience in Business Intelligence, specialising in Data, Analytics, Insights, and Automation.
Shazib has predominantly worked in the Financial Services industry, collaborating with clients spanning capital markets, energy, insurance, banking, and media segments.
His global experience includes collaborating with stakeholders from the USA, UK, Canada, UAE, Spain, and the Philippines.
A standout achievement in Shazib's career was the successful execution of the Synergy Analytics project. In this endeavour, he creatively addressed access issues, implemented automation processes, and achieved significant time savings, reducing annual workload by 500 to 600 hours.
Main expertise
- Microsoft Power BI 8 years
- SQL 5 years
- Snowflake 1 years
Other skills
- VBA 5 years
- AWS S3 3 years
- Tableau 2 years
Selected experience
Employment
Senior Manager, Business Intelligence
S&P Global - 2 years 9 months
- Implemented automated systems in Excel and Power Automate for Extract, Transform, Load (ETL) processes from 3 different sources.
- Delivered potential options and actionable recommendations, positively impacting client retention, revenue growth, and product adoption.
Technologies:
- Technologies:
- Microsoft Power BI
- SQL
- Snowflake
- ETL
- Data Analytics
- Python
- Pandas
- Data Modeling
- Team leading
Manager, Usage Analytics & Insights
S&P Global - 11 months
- Improved the effectiveness of sales and product organisations by translating raw analysis into meaningful insights.
- Developed and implemented data governance policies to ensure the integrity and security of data.
Technologies:
- Technologies:
- Microsoft Power BI
- SQL
- Tableau
- ETL
- Data Analytics
- AWS S3
- Data Modeling
- Team leading
Machine Learning Analyst, Predictive Analytics
S&P Global - 1 year
- Assisted in creating machine learning models for predicting churn risk, upsell likelihood, product recommendations, and identifying products at risk.
- Conducted statistical analyses and data modelling to discern trends and patterns within large datasets.
- Performed propensity-to-buy analyses, clustering analysis, and offered recommended actions for improving client retention and fostering revenue growth.
Technologies:
- Technologies:
- SQL
- Tableau
- ETL
- Data Analytics
- Python
- Pandas
- SharePoint
- Data Modeling
- Project management
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