BHAVAN KUMAR BASAVARAJU

• Developed AI-driven predictive models using Python, SQL (Snowflake, Redshift), and TensorFlow to forecast patient adherence and product demand, improving inventory optimization and reducing stock-outs by 18%.
• Partnered closely with product, operations, and clinical teams to gather reporting requirements, define metric logic, and iterate on dashboard design based on user feedback.
• Performed SQL-based data validation and reconciliation to ensure consistency between source systems and Qlik reports, improving stakeholder confidence in analytics outputs.
• Led analytics and reporting for a patient adherence and product demand optimization initiative, supporting clinical and commercial stakeholders with reliable, decision-ready insights.
• Designed and developed Qlik Sense applications to track key KPIs such as patient adherence rates, prescription refill trends, inventory levels, and forecast vs. actual demand.
• Built optimized Qlik data models by integrating data from Snowflake and Redshift, applying proper associations, keys, and incremental load strategies to ensure performance and scalability.
• Developed standardized KPI definitions and documentation to ensure consistent interpretation of metrics across Tableau, Qlik Sense, and executive reports.

• Built Qlik data models by integrating structured data from cloud warehouses and ML pipelines, ensuring clean associations and optimized performance.
• Partnered with stakeholders to convert analytical and ML outputs into visual insights consumable by non-technical users.
• Performed SQL-driven analysis and validation to ensure consistency between backend transformations and Qlik visualizations.
• Conducted A/B testing and comparative analysis of model performance, presenting results through interactive Qlik Sense reports.
• Assisted in documentation of metrics, business rules, and dashboard logic to promote reuse and standardization across analytics assets.

• Designed and delivered Qlik Sense applications for sales forecasting, inventory monitoring, and operational performance tracking across multiple business units.
• Collaborated with product, engineering, and business teams to gather requirements and iterate on dashboard design based on user feedback.
• Analyzed large datasets using SQL and Qlik load scripts to build scalable data models and reusable reporting layers.
• Created executive and operational dashboards in Qlik Sense and Power BI, enabling leadership to identify demand trends and reduce • stock-outs by 15%.
• Developed standardized KPI definitions and documentation to ensure consistent interpretation of financial and operational metrics.
• Supported ML-driven initiatives by visualizing anomaly detection and forecasting outputs within Qlik Sense for faster decision-making.

• 3.6 GPA
• Relevant Coursework: Big Data, Machine Learning, and Data Visualization