Vishakha Warudkar

• Developed and maintained a scalable FastAPI backend by designing REST APIs for personalized learning recommendations, TAC insights, entitlement data, and customer interactions.
• Integrated MongoDB with dependency-injected collections, implemented startup validations, and optimized query logic to ensure reliable and efficient data retrieval.
• Enhanced system traceability and stability by adding request-level logging, unique request IDs, CORS configuration, and custom validation error handling.
• Built and integrated Generative AI components using Mistral models, LangChain, and RAG pipelines to support intelligent data retrieval and personalized recommendations.
• Designed and optimized prompt engineering workflows and ML logic to improve model performance and enable context-aware automation.
• Collaborated with cross-functional teams to gather requirements, refine data workflows, and deliver tailored backend + AI-driven solutions supporting analytics and customer enablement.

• Led end-to-end delivery of analytics and ML projects by coordinating with cross-functional teams and translating business requirements into scalable data solutions.
• Mentored junior analysts in SQL, data modelling, and reporting best practices, improving team efficiency and output quality.
• Acted as the key liaison between business stakeholders and the technical team, ensuring clear communication, timely delivery, and accurate insights.
• Oversaw data quality validation across Snowflake, Databricks, and reporting pipelines, ensuring reliable and consistent analytics for decision-making.

• Worked as an Analyst in the Data Science Insights Department, contributing to data-driven decision-making initiatives.
• Performed data exploration, data quality assessment, preprocessing, model building, evaluation, and validation to support analytical and ML workflows.
• Enhanced team collaboration by effectively communicating complex insights through clear visualizations and concise reports.
• Partnered with cross-functional teams to identify process improvement opportunities and drive operational efficiency.
• Improved internal knowledge sharing by creating comprehensive documentation and SOPs for analytical tasks and workflows.

• Developed machine learning models to solve specific business problems and improve project outcomes.
• Built a House Price Prediction model using supervised learning and saved the model with Joblib.
• Performed customer market segmentation using K-Means clustering based on income and spending score.
• Handled data cleaning, preprocessing, model training, and reporting for the projects.

• Created clear visualizations and charts to present data insights to stakeholders.
• Gathered, analyzed, and documented business and project requirements with cross-functional teams.
• Identified data issues through root cause analysis and recommended corrective actions.
• Built ML models to predict student scores based on study hours and determined optimal clusters for the Iris dataset using visualization techniques.

• Managed team activities, including work allocation and daily coordination, to ensure smooth project execution.
• Conducted marketing performance analytics to provide a 360-degree view of customers and support strategic decision-making.
• Maintained sales administration records and post-sales service details using CRM tools.
• Supported business analytics initiatives by identifying opportunities to improve data usage and engagement.

• Collected and analyzed field data to generate actionable insights and support data-driven decision-making.
• Ensured high data quality through rigorous validation and accuracy checks.
• Performed trend analysis and prepared reports that improved operational understanding and forecasting.
• Collaborated with cross-functional teams to integrate field data with other datasets and enhance overall analysis.
• Provided timely technical support to improve customer satisfaction and assist team members with complex issues.

Supported departmental tasks to increase understanding of industry processes.