Shubhasmita panda

Accomplished Sr. AVP at Wells Fargo, I excel in leveraging Large Language Models and NLP to drive innovation. Skilled in Python and machine learning, I've significantly enhanced system stability and customer satisfaction. My leadership fosters a culture of continuous learning, blending technical expertise with team development to deliver impactful solutions.

Meticulous Data Scientist accomplished in compiling, transforming and analyzing complex information through software. Expert in machine learning and large dataset management. Demonstrated success in identifying relationships and building solutions to business problems.

· Executed some internal projects using tools such as Tableau for Data Visualization

· Recognized by managers, colleagues, and peers for innovation, communication, and teamwork to ensure quality, timely project completion

Certified Foundations of Data science], [Google]

Project # 1

Project Name : Loan Grader

Client  : Wells Fargo

Duration    : April 2024 to Oct 2024

Environment : Python, SKLearn Libraries, Data Visualisation Thru Matplotlib/Seaborn, Machine Learning Algorithms

Description: Predict the rating of all customers in order to decide whether he/she is a potential customer to be considered by taking the history of the transactional data which includes banking, card transactions, loans.

Responsibilities:

● Requirement discussions with the clients and also coordinating with Operations team to understand the manual work around done by the team.

● Review the estimates for work items, help the team with impact analysis and participate in estimation justification meetings with the clients.

● Identifying the points from where we need to get data sources and data consolidation process.

● Involved in Data Pre-processing Techniques such as data cleaning, visualizing the data, identifying outliers and making data ready for Machine Learning Techniques.

● Machine Learning Algorithms Evaluation.

● Analyze the results of all algorithm outcomes and deciding the best one

● Model Deployment process once signoff is in place.

Project # 2

Project Name : Document Index Processing through NLP

Duration : Oct 2023 to April 2024

Client  : Wells Fargo

Environment: Python, SKLearn Libraries, Data Visualisation Through Matplotlib/Seaborn, NLP, Machine Learning Algorithms

Description: Operations Team manually open several documents as part of their monthly process and decide which type of billing should be done. They take the figures from the respective documents and proceed with the billing process. Using NLP document indexing automated the process of document identification and this has resulted in reducing lot of FTE effort.

Responsibilities:

● Numerous discussions with Operations team and understand the process of work done

● Engaging with clients and discuss on way of approach for automating the process.

● Review the estimates for work items, help the team with impact analysis and participate in estimation justification meetings with the clients.

● Create a platform to get all the documents at one place which is used as an input for Machine Learning Algorithm

● Data Pre-processing Techniques such as data cleaning, visualizing the data, identifying outliers and making data ready for Machine Learning Techniques.

● Measure the performance of the algorithms applied and choosing the best one.

● Model deployment.

Project # 3

Project Name : Mini project on Customer behavior with change in rates

Duration : 2 months

Client   : Wells Fargo

Environment : Python, SKLearn Libraries, Data Visualisation Thru Matplotlib/Seaborn, Machine Learning Algorithms

Description: As part of this project, prediction of behavior of a customer with the revision of rates as quick grasp for end business users.

Responsibilities:

● Review the estimates for work items, help the team with impact analysis and participate in estimation justification meetings with the clients.

● Involved in Data Pre-processing Techniques such as data cleaning, visualizing the data, identifying outliers and making data ready for Machine Learning Techniques.

● Model performance evaluation and presentation to the business users.

Project # 4

Project Name : Prediction of database spikes

Duration : 2 months

Client   : Wells Fargo

Environment : Python, SKLearn Libraries, Data Visualisation Thru Matplotlib/Seaborn, Machine Learning Algorithms

Description: As part of this project, prediction of database spikes for current year based on last 5 years of data.

Responsibilities:

● Review the estimates for work items, help the team with impact analysis and participate in estimation justification meetings with the clients.

● Involved in Data Pre-processing Techniques such as data cleaning, visualizing the data, identifying outliers and making data ready for Machine Learning Techniques.

● Model performance evaluation and presentation to the business users.

Project # 5

Project Name  : SSP Automation

Duration  : May 2018-Oct 2023

Client    : Wells Fargo

Description: SSP is an automation and orchestration for day-to-day application operation such as start/stop, Fail Over, Deployment, Patching, Upgrades, wellness check etc. All these functionalities (i.e E2E, AMA, Cert Management) are done through an in-house developed drag and drop graphical user interface with a horizontally scalable backend that can handle 1200+ automation tasks simultaneously.

Responsibilities:

● Involved with microservice based applications by configuring Github, Maven, SonarQube, Jfrog, Docker and Kubernetes by creating Jenkins CI/CD pipelines for the auto build and deployments.

● Having good experience of writing Jenkins pipelines for build and deployment, docker files to build the images, manifest files to deploy in Kubernetes and ansible playbooks for configuration management.

● Preparing various reports for client status meeting.

● Having good experience with few AWS services like EC2, EKS, EBS, VPC, Route53, S3 Bucket, Cloud watch, Elastic Beanstalk, ELB and IAM.

● Participate in all AGILE SCRUM meetings and update the status of work parcel.

● Review of all the work artifacts from the team.

● Providing the test support and fixing all the defects raised.

● Implementing the changes in production system.

● Supporting and Monitoring Production batches.

● Provide maintenance support for the application which includes all the housekeeping Jobs.

Project # 6

Project Name : Risk reference and finance Role : Software Engineer

Duration : Aug 2015 — May 2018

Client   : Societe Generale global solution center

Responsibilities:

● Deliver the reports requested by End users in time without any delay.

● Taking project related calls and interacting with clients and end users directly.

● Mentoring new joiners in the project.

● There are few challenges where in there is a requirement from end users to create the reports in a customized which requires logical change in the program. Able to change the code in a less stipulated time and deliver the reports to the users at the right time without any delay.

● Automated few reports which reduced manual effort.

Project # 7

Project Name : Decentralized operations and global support Role : Software Engineer

Duration : JULY 2013 — AUG 2015

Client    : HCL Technologies Pvt. Ltd.(CITI bank projects)

Responsibilities:

• Writing and developing software code that meets the specifications and requirements of the project.
• Testing and debugging software to ensure that it functions as intended.
• Deploying software to production environments and working with other teams within the organization as needed.
• Fixing and improving existing software, including debugging existing code and adding new features.
• Collaborating with other members of the development team to ensure that code is consistent with the overall project design.
• Participating in code reviews to identify and fix potential issues or bugs.
• Keeping up-to-date with the latest software development tools, techniques, and trends.
• Communicating progress and issues to project managers, stakeholders, and other team members.
• Providing technical support to users of the software as needed.