About Me
Experienced data analyst. Skilled in creating impactful visualizations and dashboards using Power BI. Proficient in Data Analytics. Knowledge in Python, SQL, Power BI. Problem-solving ability, along with effective suppor…
Experienced data analyst. Skilled in creating impactful visualizations and dashboards using Power BI. Proficient in Data Analytics. Knowledge in Python, SQL, Power BI. Problem-solving ability, along with effective support to enable a positive work environment, enjoy creative problem solving and getting exposure to multiple projects.
Experience
Data Analyst
Worked closely with the customer groups to realize ML opportunities and build dashboards for BI solutions
Collaborated with the team to effectively perform data quality tasks. Served as the go-to person for all data-related organization and expertise as needed.
Built a performance tracker for the team ensuring smarter resource allocation leading to an efficiency of 40%
DATA ANALYST
<p>Worked closely with the customer groups to realize ML opportunities and build dashboards for BI solutions<br>
Collaborated with the team to effectively perform data quality tasks<br>
Served as the go-to person for all data-related organization and expertise as needed<br>
Built a performance tracker for the team ensuring smarter resource allocation leading to an efficiency of 40%</p>
Marketing Mix Modelling
<p>Delivered in Marketing Mix Modelling<br>
Used machine learning to uncover the advantages of media activations on sales for the Sazerac Fireball brand according to the ROI and CPM<br>
Led to an increase in the volume sales of Sazerac 361,582 L (13%)</p>
Project Davis-Bayer
<p>Supported in profile making of Bayer in respect to entire OTC market in PowerPoint<br>
Structured and validated data tables reducing error rates to 40%<br>
Responded to any request upon business information appropriately and in timely manner<br>
Ideated the reason of Bayer in the entire OTC losing its share<br>
Led to improvement in performance by 35%</p>
Ecomm Fill Rate
<p>Used SQL and Pandas to create joins of over 30 tables<br>
Used LGBM regressor for future prediction<br>
Led to an improvement in fill rate by 10% in 8 weeks across 12 sites<br>
Supported in visualization for Power BI to identify key drivers of fill rate gap at SKU and plant level<br>
Addressed the issue of low fill rates in Pepsi Co's e-commerce channel</p>