Experienced in developing advanced statistical models and machine learning algorithms using Python (Scikit-learn) to forecast service call rates and optimize production efficiency. Skilled in building ETL pipelines to handle large datasets and providing real-time insights via Tableau and Looker Studio dashboards. Expertise in creating predictive models, conducting gap analysis, and automating KPI reporting processes. Successfully improved service performance, optimized resource utilization, and increased production yield by 20% through data-driven decision-making and process improvements. Proficient in leveraging Python, R, SQL, and REST APIs for advanced data analysis.

Worked with Business Intelligence tools like Power BI Desktop, Power BI Service, and ORACLE/SQL, with experience in cloud computing architecture and multi-cluster, shared data architecture.Developed SQL queries and created relationships between datasets, leading to the creation of dashboards and visualisations for efficient data analysis and reporting.Shaped and prepared data in Power BI using advanced query tools, including DAX functions, and performed data manipulation with Pandas for in-depth analysis.Published reports to Power BI services, shared reports, and optimised troubleshooting of tiles, reports, and dashboards.Gained experience in importing data from multiple sources and creating reports based on data extracted from PowerBI servers.

Integrated SQL databases to efficiently store and manage large datasets related to project data, facilitating the tracking of design iterations, simulation results, and material properties across multiple additive manufacturing projects.Developed and automated Python scripts to perform comprehensive data analysis on experimental results, identifying trends in material properties and optimising key parameters in manufacturing processes.Conducted detailed statistical analysis of ceramic paste formulations, utilising data-driven insights to achieve 100% homogeneity by optimising variables such as rheology, printing parameters, and sintering temperature profiles.Analysed G-Code data through Python to identify inefficiencies in the material extrusion process and implemented optimised code modifications, leading to uninterrupted fabrication and production of 100% dense ceramic parts.Created data visualisation reports to present findings, enabling stakeholders to make informed decisions based on real-time analysis of manufacturing processes and material performance.

Created SQL views extensively for supporting dashboard requirements according to business needs.Built reporting infrastructure using Power BI and SQL to provide real-time insights into the product, marketing funnels, and business KPIs.Developed SQL queries to obtain complex data from tables in on-site and remote databases.Created and developed a variety of reports and dashboards, resulting in a significant 30% increase in operational efficiency.Prepared daily reports based on various analysis efforts toward improving customer experience.Developed and optimised data models using DAX queries in Microsoft Power BI to facilitate interactive and insightful data analysis.Created and refined standard queries for verifying data quality and pinpointing errors.

Owned the data analysis and reporting of sales & marketing KPIs for Suzuki’s marketing and sales app.Led the post-launch data analysis of marketing campaigns to assess campaign performance, analyze user behavior, and define customer acquisition strategies.Performed A/B testing to measure lift for campaign objectives across different user groups.Used SQL/Hive queries to extract data from multiple databases to develop Tableau/Power BI dashboards, providing a comprehensive view of campaign performance based on revenue, media channels, and customer demographics.Liaised with the data engineering team to create procedures to automate KPI reporting.Developed reports and presentations for the leadership team to provide insights on the performance of marketing efforts, using synthesised findings to enable efficient business decision-making.Worked with the leadership team to support the planning of future marketing campaigns and provided recommendations for user acquisition and retention strategies.