Bruna Goncalves
Data Scientist @ Leve Saúde | Turning complex data into actionable insights through Machine Learning, Predictive Analytics, and Business Strategy
- Role
- Data Scientist at Leve Saúde
- Location
- San Diego, CA, US
- LinkedIn followers
- 500 followers
About Bruna Goncalves
Data Science & Analytics professional (Lead Data Scientist at Leve Saúde) with 3+ years turning complex data into actionable business insights. I focus on predictive analytics, customer segmentation/clustering, and business intelligence (BI) to help organizations make smarter, data-driven decisions- Built the company’s first Generative AI / BI assistant on Databricks Genie with SQL pipelines, letting executives query KPIs in natural language - cutting manual analysis time by 50%+ and boosting cross-functional decision speed-Built a churn prediction and cluster analysis model for 60K+ customers, using behavioral segmentation and A/B testing to identify at-risk groups and recover $100K+ in revenue-Designed interactive dashboards/visualizations in Python and Power BI to monitor profitability and operational efficiency for leadership.I’m excited to apply predictive modeling, machine learning, and KPI tracking to bridge analytics with business strategy and accelerate growth.Let’s connect: b••••••••@gmail.com
Experience
Data Scientist
Oct 2023 — Present
I lead end-to-end analytics and machine learning initiatives for the entire start-up company, supporting automation, strategic metrics (CAC & LTV), and data infrastructure development. Built AI-Powered Decision Support Tool for Executives:> Developed a GenAI assistant (Llama + Genie) for executive leadership, training the model with business KPIs via Databricks SQL views, functions, and prompt optimization to power real-time insights in Streamlit.> Partnered with data engineering for API integration. Designed Churn Risk Segmentation Model:> Built model using data from 43K+ customers to predict segments most at risk for churn. Used behavioral feature engineering and evaluated multiple algorithms (LR, SVM, soft voting, decision trees, etc.) to maximize interpretability. The company used my results to reduce churn and increase revenue by $60K+ during A/B testing.
Education
Norfolk State University
Master of Science - MS, Electrical and Electronics Engineering
Norfolk State University
Bachelor of Science - BS, Electrical and Electronics Engineering with Minor in Mathematics
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