Dynamic and dedicated Data Scientist with over 1.5 years of extensive experience in developing data-intensive applications and resolving complex architectural and scalability challenges in various industries. Experienced…
Dynamic and dedicated Data Scientist with over 1.5 years of extensive experience in developing data-intensive applications and resolving complex architectural and scalability challenges in various industries. Experienced in predictive modeling, data processing, data mining algorithms, machine learning methodologies, optimization techniques, text mining, data analytics, statistical modeling, and AWS-based data analysis and visualization. Demonstrated ability in team coordination, leadership, debugging, process improvement, and using tools such as PowerBI, Tableau, Alteryx, UiPath-RPA, Azure DataBricks, Azure DataFactory, and Azure DataLake.
• Dynamic and dedicated Data Scientist with over 1.5 years of extensive experience in developing data-intensive applications and resolving complex architectural and scalability challenges in various industries.
• Expertise in predictive modeling, data processing, and data mining algorithms, proficient in scripting languages including Python, SQL, R, and Excel-VBA.
• Skilled in creating, developing, testing, and deploying highly adaptive diverse services to translate business and functional requirements into substantial deliverables.
• Strong background in machine learning methodologies, optimization techniques, text mining, data analytics, and statistical modeling.
• Proficient in utilizing AWS services, including data analysis, data visualization, Hadoop, predictive modeling, and analytics, with expertise in Big Data Ecosystem, Hadoop MR, NoSQL, Spark, and Kafka.
• Demonstrated ability in team coordination, leadership, debugging, process improvement, and utilizing tools such as PowerBI, Tableau, Alteryx, UiPath-RPA, and more.
Developed a sales forecasting model using a hybrid methodology incorporating time series analysis.
Extracted information from Azure DataLake and performed preprocessing, transformation, mining, and modeling within Azure DataBricks.
Used Fast Fourier Transform to address white noise and extract hidden trends and seasonality.
Built and evaluated AR, MA, ARMA, ARIMA, and SARIMA models for future sales prediction.
Developed LSTM and RNN deep learning models to predict future sales.
Merged additional data sources using Azure DataFactory for store manager performance assessment.
Pulled data from a container and stored it in Synapse using Linked Services.
Spearheaded automation for Daily Sales Apportionment and Reconciliation using Azure DataLake, Azure DataFactory, Azure DataBricks, and PowerBI.
Managed daily sales data across four channels and established a SharePoint drop for raw input files.
Engineered DataBricks notebooks for each channel with event-based triggers.
Stored processed data as Delta Tables in the DataLake output container.
Extracted selected columns from all channels and organized them in a SQL table.
Integrated PowerBI with the SQL table view for daily sales visualization.
Implemented an automated daily refresh mechanism in PowerBI synchronized with SQL table updates.
Crafted a dashboard featuring KPIs for daily sales metrics.
Streamlined the daily sales process, reducing manual effort and ensuring accurate, up-to-date business intelligence.
Extracted forensic data from Outlook email (.pst) files and document-type data from the C drive.
Used Python to extract content from email files and organize it into Excel for analysis.
Applied sentiment analysis to assess emotional tone and identify suspicious or fraudulent content.
Applied Benford analysis to identify anomalies and irregularities in numerical patterns.
Performed keyword analysis on email and document data to identify high-risk content and potential fraudulent activities.
Combined sentiment, Benford, and keyword analysis outcomes to detect flagged high-risk emails and patterns indicative of fraud or illegal activities.
Developed a workflow using Tableau Prep Builder to merge and transform data sourced from Salesforce and Oracle OBIEE.
Conducted data cleaning and transformation to standardize granularity for dashboards in Tableau Desktop.
Implemented the workflow on the client's server and scheduled it for daily execution.
Published the workflow output as a data source.
Delivered a visualization dashboard providing a comprehensive overview of sales data for HR representatives across diverse regions.
Led a team responsible for inspecting and implementing measures in the development, improvement, and review of new specifications and procedures for products or processes.
Trained staff in the implementation of specifications and procedures.
Completed a project titled 'Empirical study on G.R.S Industries’ and Management of ISO 9001.'
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