Senior Data Analyst
Freddie’s Flower
Total des années d'expérience :5 years, 10 Mois
● Reduced report generation time by 60 % by developing :
○ Revenue Dashboard enabling dynamic, real-time visualisation of revenue by product.
○ Marketing Dashboard enabling weekly tracking of marketing expenditures and ROI, a task
previously performed manually.
● Facilitated a 50% increase in data self-service efficiency by updating the LookML schema.
● Enabled a 15% more efficient resource allocation by developing SQL queries for a budget model.
● Contributed to a 20% decrease in customer first payment churn through a targeted CRM campaign.
● Collaborated closely with a business analyst to redefine the strategy for a key business unit.
Provided pivotal business insights and data driven recommendations contributing to a more
effective approach to market challenges.
● Executed a comprehensive customer segmentation analysis, enabling the marketing team to refine
their targeting strategies. This analysis contributed to a 25% increase in marketing campaign
effectiveness and a more efficient allocation of marketing resources to optimize efforts and budget.
● Reduced report generation time by 90% through Google Sheets and BigQuery automation.
● Automate article performance analysis from Excel to Python: 90% reduction in process time.
● Improved process accuracy by 25%, contributing to more effective inventory management.
Technical Environment:
SQL, Python, Google Sheets, MSTR, GCP.
● Involved in a successful fundraising campaign by leading a comprehensive company analysis of key
business metrics and product performance.
● Enhanced team productivity through effective management and project execution.
Technical Environment:
SQL, Superset, Google Sheets, Tableau.
● Contributed to a 30% YoY sales increase through targeted analytical support.
● Improved KPI tracking efficiency by 35% by developing and maintaining performance dashboards
and responding to analytics requests.
Technical Environment:
Plx, Google SQL, Google Sheets, Looker.
● Achieved a 90% student satisfaction rate in delivering comprehensive data analysis training.
● 70% of students secure jobs within the first three months post-training.
● Training includes SQL, Python, Google Sheets, Power BI, APIs.
● Predicted retention (94% accuracy), influencing key strategic decisions for the leadership team.
● Conduct a cross-functionally retention analysis to measure the impact of each team on retention.
● Led a 3% improvement in the self-served refund tool usage via product analysis and A/B testing.
● Worked on various analyses including retention curves, customer lifetime value, cohort analysis,
churn analysis, RFM segmentation, funnel analysis, and churn prevention.
● Developed and implemented two applications, enhancing marketing campaign success by 25%.
○ Attribution & Marketing Mix Modeling reports.
○ Campaign Pacing
● Involved in data-driven decision-making processes across marketing teams and other stakeholders.
Technical Environment:
R, Python, SQL, Rshiny, BigQuery (GCP).
Improved data classification efficiency by 30% through machine learning algorithms
● Developed a predictive model that enhanced the forecasting accuracy of best-sellers by 40%.
● Technical Environment: Python, Business Object (BO).