HI THERE
I’m Anand Vidvat,
Data enthusiast +
an Engineer.
- 3+ Experience
- 55 Analytical Projects
As a data enthusiast, I am passionate about identifing patterns in data and levergaing them to pushing the boundaries for business growth.
My mission is build impactful solutions that solve real-world problems and add value to business growth.
I am currently Interning as a Data Analyst at UF Information Technology, where I develop and visualize data-driven solutions that enhance customer satisfaction and reporting efficiency of the IT services. I use Power BI, Python, Salesforce SDK, and SOQL to create dashboards and ETL pipelines that integrate and analyze data from various sources.
I have a strong background in data engineering, having worked at HP for three years. I designed, developed, and deployed over sixty data pipelines using technologies such as Apache Spark, Python, SQL, and Delta Lake in AWS Cloud. I also built a Data Management Framework that simplified data transformation and reduced development time by 70%. I collaborated with product managers, business analysts, and data scientists to prototype data products and machine learning models while complying with data privacy policies
Developing an ETL pipeline that integrates Salesforce Case Data with Qualtrics Customer Survey Data. Additionally, I created a Power BI dashboard that leveraged the transformed data to report month-on-month growth in customer satisfaction.
worked with product managers, business analysts, and data scientists to prototype data products and machine learning models while complying with data privacy policies such as GDPR.
As part of Enterprise Data team at Hewlette-Packard, I work on developing data pipelines that provide enrichment and reference data for analytical usage also while building data platforms that support analytical workloads.
Developed a Node Instrumentation Microservice that monitors and reports resource utilization stats such as CPU usage, Memory usage, Disk, and Network bandwidth utilization in a Linux System. .
Built a 3D CNN model using the Caffe2 framework over on-premise cluster. The deep learning model was trained on image data (over a million data points) for action recognition through Transfer learning and fine-tuned through the adversarial Learning paradigm.
Master of Science in Information Systems and Operations Management, Specialization in Data Science, GPA : 3.88/4
Bachelor of Technology in Information Technology, GPA : 3.77/4
Built a Question-Answer Bot which is runs on a LLM based model (OpenAI's gpt-3.5) to analyse tesla 10K filing for FY2023
The LLM model uses Retrival Argumentative generation (RAG) to answer imprompt questions
