Paramvir Singh Bali

GuruSchools is one of the leading IT consulting and Outsourcing Partner, offering services to Fortune 500 companies in Banking, Automotive, Insurance, Entertainment, Media, Oil, Power, Utility, Manufacturing, Retail, Telecom, Pharma, Real Estate, Services domains etc.

The PNC Retail Bank supports the financial needs of millions of individuals, families and small businesses, and fosters lifelong banking relationships built on expert advice and financial solutions across deposits, payments, personal lending, credit card, wealth advisory and brokerage.

Project Scope: Gather and optimize client data to help make informed financial decisions by utilizing artificial intelligence and machine learning to detect/forecast financial fraud, anomaly detection, liquidity needs, improve collection strategies, expand credit decisions, mitigate risk and reduce costs.

Responsibilities:

· Built machine learning models to identify whether a user is legitimate using real- time data analysis and prevent fraudulent transactions using the history of customer transactions with supervised learning.

· Automated the loan eligibility process (real time) based on customer details on online forms like gender, marital status, education, number of dependents, income, loan amount, credit history, and others. Identified the customer’ segments, those are eligible for loan amount so that we can specifically target those customers.

· Involved in different phases of data acquisition, data collection, data cleaning, model development, model validation, and visualization to deliver solutions.

· Worked with Python NumPy, SciPy, Pandas, Matplotlib, and Stats packages to perform data manipulation, data mapping and data cleaning.

· Participated in features engineering such as feature generating, PCA, feature normalization and label encoding with Scikit-learn preprocessing.

· Developed various machine learning models such as Logistic regression, KNN, and Gradient Boosting with Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn in Python.

· Trained Random Forest algorithm on customer web activity data on media applications to predict the potential customers. Worked on Google TensorFlow, Keras API- convolution neural networks for classification problems.

· Performed univariate and multivariate analysis on the data to identify any underlying pattern in the data and associations between the variables

· Conducted analysis of customer behaviors and discover the value of customers with RMF analysis; applied customer segmentation with clustering algorithms such as K-Means Clustering, Hierarchical Clustering, and Gaussian Mixture Mode

· Data was trained and tested using various Machine Learning algorithms like Linear & Logistic Regression, Naïve Bayes, Decision Trees, Random Forests, Clustering, SVM, Neural Networks, Principal Component Analysis, and Bayesian.

· Experimented with ensemble methods (Random Cut Forest, eXtreme Gradient Boosting) to increase the accuracy of the training model with different bagging and boosting methods and deployed the model on AWS.

· Built real-time Data Visualizations Dashboard on transaction data, as the end-user transactions are live scored for Fraud using AWS SageMaker ML endpoints.

· Evaluated models’ performance using Accuracy, F-Score, AUC-ROC, Confusion Matrix, Precision, and Recall evaluating different models’ performance

· Designed rich data visualizations to model data into human-readable form with Power BI and Matplotlib.

· Created and maintained reports to display the status and performance of deployed model and algorithm with Power BI.

Environment: Python, NumPy, Statistic, Pandas, SciPy, SQL Server, PySpark, SparkSQL, Seaborn, Power BI, Machine Learning (Logistic regression/ Random Forests/ KNN/ K-Means Clustering/ Hierarchical Clustering/ Ensemble methods/ Collaborative filtering), GitHub, Docker, API Gateway, Lambda Function etc.

Anderson Merchandisers is a leading name nationwide, in merchandising services, groceries, pharmaceuticals, hardware, electronics and more. To ensure best ROI, Anderson uses value-centered reporting and analytics to monitor and interpret data across your merchandising activities and provide you with the metrics necessary to maximize results.

Project Scope: Design and implement data collection systems and strategies to provide comprehensive in-depth data analysis, develop reports and build execution dashboards to support both Supply Chain and Finance streams. Provide real-time dashboards, OSA reporting, execution summary and performance trends to detect growth opportunities, measure visit impact, and correct on-shelf opportunities and inventory discrepancies while prioritizing ROI and sales uplift at store level.

Responsibilities:

· Worked with the business users to understand the architecture, data model, business logic and rules to be applied to meet the business needs.

· Performed data analysis and maintenance on information stored in MySQL, MS SQL server, Mongo DB, Cassandra Database.

· Used SQL complex queries, Subqueries, Stored Procedures, Triggers and packages for data manipulation and data extraction in RDBMS databases with structured data in different formats (Relational-SQL file extension, CSV, Excel) or from various servers.

· Built various graphs for business decision making, solving problems and data exploration/ analysis using Advanced Excel (VLOOKUP, XLOOKUP, Macros, Formulas, Functions, Pivot chat, tables and diagrams, Power View, Power Map, Heat Map).

· Performed statistics technique and hypothesis test including ANOVA test, T test, F test, A/B test in Excel to prove the business assumption through data-driven analysis using Excel.

· Used Power BI, Power Pivot to develop data analysis prototype, and used Power View and Power Map to visualize reports.

· Used DAX table functions including FILTER, ALL, VALUES, DISTINCT and RELATEDTABLE. Used Z-order to overlap the reports on each other using Power BI.

Environment: MS SQL Server Management Studio 2016, SQL, MS Visual Studio (ETL), MS SQL Server Integration Services (SSIS), Power BI, MS SQL Service Analysis Services, Excel, MongoDB, Cassandra, Windows

Unisys Corporation is an American multinational information technology (IT) services and consulting company founded in
1986 and headquartered in Blue Bell, Pennsylvania. The company provides digital workplace, cloud applications & and
infrastructure, enterprise computing, processes, and data analytics services.

Project Scope:ClearPath ePortal is a comprehensive solution designed to modernize and extend the capabilities of existing ClearPath server applications. It enables organizations to bridge their traditional server applications with modern web, mobile, and service-based architectures without needing to modify the original applications.

Responsibilities:

• Gathered data and project requirements from users and management within the banking domain, dealing with
datasets comprising over 1 million customer records.
• Analyzed and evaluated financial data/information from multiple banking systems, reconciling conflicts and
addressing complex business issues related to credit, risk, and customer behavior.
• Identified, analyzed, and interpreted trends or patterns in intricate financial datasets; developed advanced graphs,
reports, and presentations to illustrate customer behaviors and market trends.
• Designed and built robust datasets and data solutions, successfully migrating large volumes of sensitive financial
data into readable formats across various banking interfaces.
• Performed comprehensive data analysis, including data cleaning, transformation, and integration, facilitating the
smooth execution of data imports and exports within the banking systems.
• Conducted thorough data quality assessments and root cause analysis using SQL on banking source data, ensuring the highest levels of accuracy and compliance with financial regulatory standards.
• Developed and implemented best practices, processes, and standards for data migration within the banking sector,
collaborating with cross-functional teams to comprehend data utilization and implications for system-wide data migration.
• Provided critical statistical support to the banking sector by performing advanced mixed-model analyses using R,aimed at predicting customer behaviors and aiding in strategic decision making.

Environment: SQL, Tableau, MS Office (Excel, PowerPoint, Word).

Project Scope:

Analyzing international money transfer at ICICI Bank's New York branch to diverse destinations. Leveraging data analytics to understand transaction patterns, enhance fraud detection, and optimize operational efficiency for improved customer service.

Worked on Money2India (www.money2India.com) money remittance system. This role entails providing support to the Business Development team, including tasks such as researching, analyzing, modeling future growth opportunities, and crafting presentations for management.

Responsibilities:

● Worked closely as a team player to develop and design best in class databases for Money Transfer(e.g., NEFT, RTGS, IMPS).
● Define the data needed for valuation analysis including name and address, amount of the wire transfer,account number and account type, bank routing number, and bank's SWIFT or BIC code.
● Created complex custom data queries and procedures in SQL for Money Transfer datasets.
● Worked with Data Scientist team on data cleaning and ensured data quality, consistency, integrity, performance of data models.
● Worked with the business intelligence reporting team to generate reports and visualizations in Tableau.
● Conduct Market analysis for potential targets including competitive behavior and alternative strategies.
● Prepare analysis and presentation of business cases for proposed projects to present to the Business Development team.
● Maintain detailed knowledge of the customer contracts to assist the customer and operations in ensuring
support to the terms.

Environment: SQL, Tableau, MS Office (Excel, PowerPoint, Word).

Novagen Healthcare Pvt. Ltd. is a multinational corporation that provides scientific research services, equipment, consumables, and software to laboratories worldwide. They offer a wide range of products and services in various scientific fields, including biotechnology, pharmaceuticals, and healthcare.

Project Scope: The work focused on gathering and cleaning internal data for standardization and costcalculation, providing market data analysis for monitoring laboratory equipment sales and providing data support for higher management departments to make business decisions.

Responsibilities:
● Analyzed massive medical data from multiple sources, consulted on checking and standardization with
product departments and analytic teams to discuss the metrics for gathering data and the database structures.
● Analyzed data using by SQL.
● Provided expertise and translated the business needs to design.
● Created client requested metrics, and dashboards for insights and data visualizations using MS PowerBI.
● Performed data preprocessing like cleaning (for outlier, missing values analysis, etc.) and Data Visualization (Scatter Plots, Box Plots, Histograms, etc.) using Matplotlib.
● Analyze data to evaluate sales performance and provide recommendations to grow market share and revenue.
● Communicated with medical departments on the features and dimensions of the data needed and worked with technological teams for solutions to improve internal data gathering systems and databases.
● Responsible for compiling, analyzing, and reporting pharmaceutical market data to provide valuable
feedback and actionable insights.
Environment:: SQL, MS Power BI, MS Office (Excel, PowerPoint, Word)

Maa Bhavani Developments Headquartered in Vadodara, Gujarat, is a prominent real estate investment company specializing in multifamily properties. The company excels in real estate development and property management, prioritizing the creation of high-quality living spaces. Additionally, Maa Bhavani Developments is actively involved in community initiatives, fostering a positive impact beyond its developments.

Project Scope: The team was responsible for developing and designing databases for valuation of Residential Real Estate and providing expertise and translating the business needs to design; and develop tools, techniques, and metrics, and dashboards for insights and data visualizations.

Responsibilities:

● Create detailed documentation of business requirements, process flows, and data specifications for the valuation project.
● Define the data needed for valuation analysis including property details, market trends, and comparable sales data.
● Created complex custom data queries and procedures in SQL for Residential Real Estate datasets.
● Managing and coordinating the activities of construction teams, including laborers, subcontractors, and other personnel.
● Ensuring that construction work meets quality standards and specifications.
● Communicate with clients, architects, engineers, subcontractors, and other parties to coordinate activities and resolve conflicts.

Environment: SQL, MS Power Bi, MS Office (Excel, PowerPoint, Word) & Communication skills