DEVENDRA RAJPUROHIT

• Diners device Tokenization : - To enable Tap & pay for customer using Device for Diners.
• CCD - DCLMS : - Credit card decline management system to enhance the customer journey by communicating the decline reason through SMS/Email/Whatsapp for increasing the daily credit card limit.
• Diners Alt Id Interoperable Solution : - To Accepting the payment through MPGS/MIGS for Diners.
• Annual Audits : - RBI, SAR, DPSC, External Audit for application COF Tokenization.
• SI HUB : - Changed the SMS communication template for Standing institutions Transaction.
• Collecting Requirements from Stakeholders, Prepare the Required Documents, FSD, UAT testing , SIT Testing, CUG Testing, ISG/Audit Sign-off, Go live.
• Analyzed the critical production customer facing Issue and resolve with in TAT.
• Implemented best-practice methodologies that improved overall project delivery timelines while maintaining quality standards.
• Interacted with internal customers to understand business needs and translate into requirements and project scope.
• Collaborated with stakeholders to define project objectives and criteria.
• Increased efficiency in resource allocation by conducting detailed business requirements analysis.
• Collaborated closely with stakeholders to identify opportunities for process improvements and drive continuous innovation in the organization.
• Reduced operational costs through thorough data analysis and implementing cost-effective solutions.
• Developed high-quality documentation to support training efforts, helping employees fully understand new systems and procedures.
• Actively participated in team meetings to share knowledge, exchange ideas, address challenges, and collaborate on potential solutions.
• Enhanced company-wide decision-making by developing comprehensive reports on key performance indicators.
• Managed vendor relationships to negotiate contracts, secure favorable pricing, and ensure timely delivery of products or services.
• Analyzed data to identify root causes of problems and recommend corrective actions.

Steps followed to implement the predictive model:

• · Models implemented
• · Logistic Regression
• · Support Vector Machine
• · Random Forest
• · Decision Tree
• · MLP Classifier
• Generated standard and custom reports to provide insights into business performance.
• Aggregated data from various sources to construct streamlined data pipelines.
• Supported tasks related to SharePoint development and application maintenance.

• Identified, analyzed, and interpreted trends or patterns in complex data sets by finding correlations and visualizing with charts.
• Identified trends and patterns in complex datasets through exploratory data analysis, leading to actionable insights.
• Applied machine learning algorithms to enhance analytical capabilities and uncover hidden patterns within the data.
• Enhanced data visualization capabilities for better decision-making with the use of advanced BI tools.
• Developed data mining algorithms to identify and classify patterns in data.
• Conducted thorough data validation and cleanup, ensuring accuracy and reliability of datasets used for analysis.
• Developed custom algorithms to optimize and automate data analysis processes, resulting in improved efficiency.
• Performed Model : - EDA & Feature Engineering, QDA, Random Forest Model, Linear Regression, Logistic Regression