Business Data Analyst

Visesh Kumar Jaiswal

adxhyy@r.postjobfree.com

414-***-****

https://www.linkedin.com/in/visesh-kumar-jaiswal/

PROFESSIONAL

SUMMARY

Analytical and detail-oriented business data analyst with experience in translating complex financial data sets into actionable insights. Proficient in utilizing advanced statistical and data analysis techniques to identify trends, patterns, and opportunities that drive informed business decisions. Skilled in data modeling, data visualization, and reporting, using tools such as SQL, Python, and Tableau. Strong problem-solving abilities combined with excellent communication skills to effectively collaborate with cross-functional teams and stakeholders. Committed to delivering accurate, timely, and impactful analytics solutions that optimize operational efficiency and support organizational growth. Adept at working in fast-paced environments and adapting to evolving business needs. Seeking to leverage expertise and contribute to data-driven decision- making within a dynamic organization.

EDUCATION

Master of Science Data Science 06/2021

University of Massachusetts, Dartmouth GPA: 3.717

Bachelor of Engineering Computer Science & Engineering 05/2019 Ramaiah Institute of Technology, India GPA: 4.0

COURSE WORK Advance Data Mining, Database Systems, Advance Machine Learning, Applied Business Analytics and visualization, Artificial Intelligence, Data Visualization, High Scientific Computing, Bayesian Statistics

(Sampling, Hypothesis testing, regression & classification), Computational Mathematics, Deep Learning, Optimization Technologies

TECHNICAL

SKILL & TOOLS

SQL (Structured Query Language), Python, C/C++, R Programming, Tableau, Power BI & Excel (for data visualization, analysis, reposting and interactive dashboards) ETL (Extract, Transform, Load) process (tools like Matillion and SSIS), Data cleansing & preprocessing techniques, Data Warehousing (such as Snowflake, Oracle and Google BigQuery) Statistical Software (SAS), Regression analysis, Predictive Modeling, Hypothesis testing, Machine Learning Algorithms (SVM, Random Forest, Naïve Bayes, Decision tree, regression, classification etc.), Jupyter Notebook/Jupyter Lab, SAS Viya, Google colab Relational Database, Data Querying & Optimization, Data Pipeline development and automation (AWS like Redshift, Glue), Data Governance and security, Data Extraction and Transformation Data storytelling, Dashboard design, Data reporting tools (Tableau, Power BI, Qlik), Data Exploration and pattern insights, KPI’s (Key Performance Indicators), data analysis, scripting & automation. WORK

HISTORY

Business Data Analyst – People’s Credit Union, Rhode Island 06/2021 – Current

• Gathered user requirements, analyzed and designed software solutions based on the requirements for various departments of the organization.

• Collaborated with database engineer to implement ETL process, wrote and optimized SQL queries to perform data extraction and merging from cloud-based server database.

• Created database objects like tables, views, procedure, triggers and function using T-SQL to provide definition, structure and to maintain data efficiently.

• Building, publishing customized interactive reports and executive dashboards, report scheduling using tableau server.

• Implemented Machine learning algorithms, random forest and support vector machines to predict a customer credit history and payment activity on historical data to get predicted label whether the customers are eligible for loans based on the credit score and report the marketing team.

• Developed story telling dashboards in Tableau desktop and published them on to tableau server which allowed end users to understand the data on the fly with the usage of quick filter for on-demand needed information.

• Developed SQL scripts to insert/update and delete data in cloud-based database tables.

• Created various ad hoc SQL queries for custom reports, executive/management reports and report types like tables, matrix, sub reports and others.

• Worked on data verification and validations to evaluate the data generated according to the requirements to be appropriate and consistent.

• Training other people in the company for tableau explorer, responding to queries via chat/email and phone.

• Collaborated with business stakeholders to understand their needs and challenges, identify data-driven opportunities, and provide insights to drive strategic initiatives and improve business decisions.

• Ensured data quality by implementing data validation and quality checks. Identified data discrepancies and anomalies, investigated data issues, and worked with relevant business stakeholders to resolve them.

• Monitored and tracked business performance metrics, such as sales, customer acquisition, and retention. Also identified KPI’s and developed tracking mechanisms to measure progress and identify areas for improvement. Research Assistant – University of Massachusetts 03/2020 – 10/2020 Worked as research assistant under Dr. Scott field on “A genetic-algorithm-optimized convolutional neural network for gravitational wave classification”.

• Gathered relevant information and background knowledge on the topic of research. Identified key studies, articles, and sources that are pertinent to the research project.

• Tried to optimize the model performance by changing 100’s of parameters needed to train the model and trying to get the best performing one.

• Contributed to data analysis by conducting statistical analysis or qualitative analysis of the complex collected data.

• Participated in the development of research design and methodology. Assisted in developing research questions and selecting appropriate research methods and tools.

• Contributed to the preparation of research reports, manuscripts and presentations. Helped in organizing and structuring research findings, writing sections of the report, and creating visual aids for presentations.

• Assisted in administrative tasks related to the research project, such as scheduling meetings, coordinating logistics, maintaining research equipment or supplies, and tracking project progress. STEM Tutor – University of Massachusetts 09/2019 – 04/2021

• Explained complex STEM concepts (like calculus, hypothesis testing, data visualization tools, physics motion, coding questions etc.) in a clear and simplified manner, ensuring that students grasp fundamental principles and theories.

• Assigned practice questions, problems, exercises and experiments to reinforce concepts and develop problem solving skills.

• Helped students develop effective study habits, time management skills, and organizational techniques. Also assisted in prioritizing tasks, setting goals, and maintaining a structured approach to learning.

• Motivated and inspired students, instilling confidence in their abilities to succeed in STEM subjects. Encouraged a growth mindset, foster a positive attitude towards challenges and celebrate student achievements.

• Updated myself with current trends, concepts and achievements in STEM subjects. Data Intern – SAIL JH, India 05/2018 – 07/2018

Collected and analyzed data from blast furnace and other machinery related to processing of steel. Our team analyzed the growth in production based on the inference from the results. Created a interactive report for easy understanding using Power Bi tool.

ACADEMIC

PROJECTS

CERTIFICATION

S

1.Patient Perceived Quality care in US Hospitals New England In this project, we are measuring patient perceived quality of care in new England by using twitter data. Our Objective is to use twitter as a supplemental data stream for measuring patient perceived quality of care CERTIFICATIONS in New England hospitals and compare patient sentiment about hospitals with established quality measures. We used Natural Language Processing to measure the sentiment of all patient experience tweets.

2.Railway Reservation System in DBMS

An application which enabled a user to get train seat and fare details between stations, book and cancel the tickets, allow administrator to enter or edit train details and manage passenger data. The following were used: Java, MySQL, HTML & CSS

3.Baseball Project

A model coded in R analyzes data of baseball players recorded from Slide tracker and predict the pitch type of the ball even before the pitch is thrown. Firstly, we have a model which predicts the pitch type of the ball with good accuracy. Then we applied naïve Bayes classification along with some extra features added, which predicts the probability of every pitch type of a pitcher. A lot of useful visualization has been done which can help the batter and pitcher to improve their performances. The following is being used: R & Python (for visualization)

4.SQL Engine design

Developed a java application which parses SQL queries and outputs the result from multiple tables with millions of records in an optimized time. Extended Hash Join Algorithm has been implemented for optimization. IN, EXISTS, Multiple sub queries, joins etc. has been implemented. It is coded in Java programming language.

5.Exploring RNN for text prediction

In this project, we created a text prediction model which predicts a text based on a given dataset. Character- level RNN (Recurrent Neural Net) & LSTM (Long Short-Term Memory) has been used. The model’s accuracy increased highly after 20,000 epochs. It was coded in python using pyTorch ML package. Platform used was Google Colab

6.Document Title Retriever

The aim of this project is to build a prototype of a title retriever which works on millions of Wikipedia pages

(which are in XML format) and returns the top ten relevant Wikipedia documents that matches the input query. The approach adopted to implement this project is method of indexing and searching. Our project takes Wikipedia corpus in XML format which is available at wikipedia.org as input. Then it indices millions of Wikipedia pages involving a comparable number of distinct terms. Then given a query, it retrieves relevant ranked documents and their titles using index. It was coded in Java. 7.Parallelizing Quicksort Algorithm using PSRS & MPI In this project, parallelize the process of sorting with the Quicksort algorithm of the numbers randomly generated. Parallel Sorting by Regular Sampling (PSRS) algorithm is being used to obtain the parallelization of the Quicksort algorithm. Implemented this concept with MPI parallelization in C. Performance metrics such as speedups and scaling test (Strong and Weak) to determine the performance of the algorithm developed are being calculated.

8.Credit Card Fraud

A huge dataset that contains transactions made by credit cards in September 2013 by European cardholders given and it presents transactions that occurred in two days, where we have only 0.172% positive class (fraud). The rest are negative class (no fraud) The dataset was highly unbalanced, and the attributes were highly correlated. To over this correlation, dimensionality reduction technique is being used. To resolve Data Imbalance, kNN algorithm was used. Various ML algorithms have been applied and more than 99% accuracy has been achieved by XGBoost algorithm. It was coded in R. 9.Netflix Movie Recommendation

Created an interactive platform with D3js visualizations to answer analytical questions based on Netflix movie data. Performed data cleaning, merge, group by, sort on python with libraries: pandas, NumPy NPTEL certification course in Design and Analysis of Algorithms. NPTEL certification course in Database Management System. NPTEL certification course in Business Analytics with R. Online Data Analytics training from Intern Shala.

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