In my role as Head of Growth and Analytics at Loops, I drive the strategic direction and execution of our PoC initiatives. My key responsibilities include:Leading the PoC Department: Manage a team of analysts to deliver impactful results and demonstrate value to prospects.Customer Engagement: Work closely with clients to optimize their KPIs through tailored data insights and solutions.Growth Strategy: Design and inspire product action items and experiments to foster growth for global companies.Technical Integration: Oversee and preform technical integrations and complex logics to ensure smooth and effective implementation of our solutions.Advanced Analytics: Analyze A/B tests using Bayesian statistics to enhance performance and drive decision-making.AI & ML Utilization: Leverage AI and various machine learning models to extract actionable growth insights.Process Optimization: Develop and refine frameworks and processes to streamline pre-sale, PoCs, and optimize Loops conversion rate.Technical Skills: Python and SQL expertise underpin my analytical capabilities, while my leadership and innovation drive the team and product strategies forward.Let’s connect and explore how we’re transforming data into actionable growth opportunities at Loops!

Established and executed a strategic domain road-map, identifying cross-departmental business opportunities, deploying machine learning models, Leveraging deep business and user understanding, and successfully gaining stakeholder buy-in to adopt data-driven solutions within the company.Achievements: Developed AI-driven forecasting model with ~20% MAPE, optimizing supply chain costs and ensuring precise sales predictions.Developed a cost-effective marketing email recommendation system using Google Cloud models, replacing an expansive third-party solution. Led implementation of real-time predictive machine learning models to personalize website experience, increase conversion rate, and boost average order value.

Implement a robust A/B test analysis methodology leveraging Bayesian Statistics. This approach enables shorter test duration by incorporating prior data while maintaining statistical validity and reliability. Implementing predictive ML models. Recruit and mentor junior data analysts, fostering professional growth.

•Leading data-driven projects from definition to execution: defining data structure, set KPIs and goals, evaluate experiments, monitor key product metrics, analyze and find actionable insights.•Managing the information collected from the site. Determine data structure (EEC, Events) and data pipeline (GTM, DL), write R&D tasks (JIRA), prioritize tasks, test in production, perform analysis.•Develop ETL processes, build data sets and analyze data using complex SQL queries. (GCP)•Develop dashboards in Tableau for monitoring and analysis of data.•analyze the site A/B tests, define and maintain a framework for statistical analysis.•Managing the Analytics Front-end team and working regularly with R&D.•Site Performance measurement & analysis: Web vitals, LCP, FID, etc.•Understanding user behavior, funnels, features and work as a key member of the product team to solve problems and identify trends and opportunities.•Ongoing work with various departments including senior management.

Mathematical department - Linear Algebra

NBO & Campinas management & digital products •Owning, analyzing, and improving the NBO model.•manage and operates a campaign system and analyzing campaign results.•Using SQL procedures for automating manual processes, and documentation of processes.•Analyzing and generating periodic reports for senior management.