Sylron Fernandes

1. Real-Time Marketing:

• Developed a code using Apps Script to send real-time contextual push notifications to sports enthusiasts during the

Asian Games 2022, resulting in a 60% increase in sports viewership, a 4% growth in subscription revenue, and a

152% rise in click-through rate (CTR).

• Awarded "Best Use of MarTech-Media & Entertainment-Including OTT Platforms" at the MarTech India Awards 2023

for the implementation of the project for Sony Liv.

2. Episodic Dropoff:

• Created an Episodic Dropoff Journey, sending personalized push notifications to customers who stopped watching a

series after a certain episode, reducing the episodic drop-off rate by 5%.

3. Churn Prediction Model:

• Created Renewal Model with 76% accuracy using Python, identifying key factors influencing customer churn and

informing retention strategies.

4. Revenue Projections:

• Utilized advanced analytics techniques to develop precise revenue forecasting models, providing crucial insights to

inform strategic decision-making processes. Consistently achieved revenue projections at an impressive accuracy rate

of 80%-90% of the targeted goals, demonstrating proficiency in data analysis and predictive modeling.

5. Campaign Performance:

• Conducted in-depth analysis of campaign performance and established dynamic KPI tracking systems using Google

Data Studio and Tableau. Also Automated all engagement reports using python.

6. Automation:

• Automated generation of all engagement reports utilizing Python scripting, streamlining data analysis processes, and enhancing

efficiency. This initiative optimized workflow and reduced manual effort, showcasing proficiency in Python programming for data automation.

1. Dashboard Creation:

• Spearheaded the creation of complex dashboards for multiple teams, leading to:

• 30% increase in data accessibility.

• 25% improvement in decision-making efficiency.

2. Automated Report Generation:

• Implemented streamlined process for automated report generation using Python and Google Apps-Script, resulting in:

• 50% reduction in report creation time

•Saving of 15 hours per week across the teams.

3. Predictive Model Development:

• Developed a predictive model using decision tree algorithms in Python to optimize account allocation, resulting in:

• 20% increase in revenue

• 15% improvement in customer satisfaction scores.

4. Data Cleaning Automation:

• Automated data cleaning processes, reducing data errors by 70% and enhancing dashboard accuracy.

5. Streamlining Process and New Dashboard Creation:

• Streamlined a process and automated reports using Python.

• Created a dashboard for a newly started team.

6. Data Management:

• Maintained rigorous data management practices, ensuring data integrity and reliability for all reports.

1. Reporting and Compliance Management:

• Generated and delivered Monthly MIS reports for broker commissions and regulatory reports to IRDAI, ensuring accuracy and

compliance.

• Maintained Excel reports for bank receipts in the IRWS system, ensuring precise financial records and reconciliation.

2. Data Analysis Support and Query Resolution:

• Provided prompt resolution to broker queries related to commission pay-outs, ensuring efficient operations and client satisfaction.

1. Reporting and Compliance Management:

• Attended to clients and investors at the front desk, providing assistance and addressing inquiries to ensure excellent customer

service.

•Handled queries from investors and distributors, resolving issues promptly and providing accurate information to maintain positive

relationships and trust.

2. Application Processing and Data Management:

• Processed applications and performed Know Your Customer (KYC) procedures, ensuring compliance with regulatory requirements

and smooth processing of client accounts.

• Maintained daily records of transaction counts, walk-ins, and other relevant data at the branch level, facilitating performance analysis

and decision-making.