• Working on the Social Media User Categorization Project, a system that categorizes users based on their activities, interactions, and feed searches.• Data mining from social media platforms involves data going through data preprocessing, EDA, removing noise, and validating results in the form of insights & dynamic reports.

The ISCC department deals with GOC-funded social programs such as EI, CPP, Passport Services, and the Canada Dental Program to take smart data-driven decisions leveraging analytical space.• Engineered Azure Data Factory (ADF) scalable pipelines for efficient data ingestion from Azure Blob and orchestrating the storage of the processed information in a data warehouse.• Handled the inflow of raw data by implementing data warehousing solutions to convert flat files into tabular format using Azure Synapse.• Identifying issues in data, working on the bugs, and aligning architecture with business needs.• Developed stored procedures (SPs) in MS SQL Server for data transformation, extracting fact-dimension tables, and documenting watermarks & failed logs.• Crafted interactive dashboards and reports in Power BI (data flows, Power Query, and DAX), delivering actionable insights & predictions to government officials on workforce utilization within the GOC.• Implemented test scripts for integration & regression testing in DevOps to ensure robustness and reliability.• Solving on average more than 5 tickets a day and pulling requests more than 3 on a daily basis.• Agile Methodologies: Applied Agile methodologies for efficient requirement gathering, analysis, and sprint planning, ensuring flexibility and responsiveness.Key Achievement: Reduced the cost of pipeline run-time & down-time by ~18% and ensured accurate and timely metrics in the dashboard via thorough testing and issue fixes

With a presence in 20+ countries, Axtel has delivered cost-effective food processing solutions to 300+ clients across the globe using PLC-generated data & market analysis.• Optimizing the client’s supply chain by forecasting shipments on a MoM basis with a MAPE error of ~25%.• Performing thorough analyses and interpretations of complex data from PLCs using ML algorithms with the aim of business upliftment through actionable insights.• Developed a Power BI interactive dashboard end-to-end to act as a back-testing toolkit that included KPIs, dynamic charts, and automated notifications for significant deviations, prompting a reevaluation of the model’s effectiveness.• Owned client calls to brainstorm further possibilities to uplift the production model and minimize the error.• Identifying the relationship between attributes and target variables, we developed a short-term model that outputs inventory predictions for raw materials.Key Achievement: Reduced inventory costs by ~10% as the client leveraged the shipment predictions to prepare for it 2 months in advance.

Dominating in the automated packaging industry with a presence in 100+ countries, product innovation based on customer feedback analysis & data insights.• Developed monthly dashboards using Tableau, pointing out the KPIs to shoot up the customer acquisition rate.• Worked extensively on developing sentiment analysis models using the TextBlob library and deep neural networks (TensorFlow and Keras).• Built a classifier model (SVM, KNN, Ensemble) to identify if a client would be a potential customer, resulting in ~10% YoY revenue growth.• Built a predictive model for load analysis within Apache Spark, A/B testing for final model selection, and testing its efficacy.• Performed market mix modelling for clients at the global level to adjust business levers to increase profit and revenue.Key Achievement: The acquisition rate grew by ~7% upon acting on the right set of identified KPIs & market trends.

Commissioning of heavy vessels, including spheres, exchangers, heaters, chimneys, columns, compressors, etc., as per safety standards and the C&I department. • Examining & certifying the various Non-Destructive tests (NDT), such as radiography, ultrasonic, leak tests, magnetic flux testing, etc.• Experienced in supervising the shutdown of various plants like polypropylene (PP) and polyvinyl chloride (PVC). Low-density polyethylene (LDPE), polybutadiene rubber (PBR), DM water, etc.• Worked extensively on the giant "Hyper Compressor," a high-pressure reciprocating compressor used to form LDPE granules from ethylene.• Knowledgeable about safety and fire standards, ASME codes, material grades, and pre- and post inspection of job work.Key Achievement: Coordinated the project of installing the hypercompressor reserve tank, which increased the production capacity by 250 metric tonnes (23% increase) of ULDPE.