Prakhar Srivastava

Long Beach, CA ***** Ph: 562-***-**** Email: adym9g@r.postjobfree.com LinkedIn Git:prakharsri307 Trailblazer: psrivastava4 EDUCATION

M.S. Computer Science California State University Long Beach Aug 2021 – May 2023 B. Tech Information Technology Galgotia College Of Engineering & Technology, India Aug 2014 – May 2018 TECHNICAL SKILLS

• Programming Languages: Java, Python, C, HTML, CSS, JavaScript.

• Frameworks and Libraries: Spring, Hibernate, Django, Flask, NumPy, Pandas, TensorFlow, Bootstrap, Reacts.

• CRM: Salesforce, Lightning Aura Components, Lightning Web Services (LWS), Apex, SLDS, Visualforce, Heroku

• Tools: VS Code, Data loader, Workbench, ANT, JetBrains PyCharm, GIT.

• Database/ Methodologies: SQL, SOQL, SOSL, Postgres, Agile/Scrum. PROFESSIONAL EXPERIENCE

Graduate Research Assistant Sep 2022 – Nov 2022

• Developed the UI of a crack detection app that detects cracks on road on basis of color using HTML/CSS and JavaScript.

• Build responsive, cross-browser compatible user interfaces using Bootstrap that significantly improved the user experience.

• Optimizing website performance and load times using advanced techniques such as lazy loading, minification, and CDN caching.

• Hosted the crack detection app on local server using flask and Jinja templates Programmer Analyst, Cognizant Technology Solutions Aug 2018 – July 2021

• Created web portal using Lightning Aura Components, JavaScript, HTML, and CSS to display balance sheet & customer information.

• Implemented declarative automation tools like Process Builder and Flow to streamline and automate business processes, significantly enhancing operational efficiency for end-users. This automation reduced manual effort and improved overall productivity.

• Leveraged Salesforce Sales Cloud and Service Cloud to set up and optimize case management, knowledge base, automation workflows, and reports/dashboards, resulting in enhanced customer support,

• Led a team of 4 professionals in migrating the HCM Consent portal from Visualforce to Lightning Aura components, resulting in a 30% increase in application responsiveness for a seamless user experience.

• Utilized Apex Controllers to retrieve data and interact with Lightning Applications, leveraging Aura Framework, Aura Attributes, and Handlers. Leveraged these tools to build robust and efficient functionalities, ensuring smooth application performance.

• Experienced in data migration using bulk API and deployment activities, with tools like Chainset, ANT, and Workbench. Maintained high data quality and system integrity (<1% defect leakage).

• Implemented CRM solution, increasing lead conversion rate by 25% and driving 15% sales revenue growth. Integrated data into Salesforce through REST and SOAP APIs using Apex classes and Triggers for actionable insights.

• Proficient in software development lifecycle, including database development and design patterns, ensuring successful project outcomes aligned with business requirements.

• Collaborated effectively with Agile development teams using SCRUM methodology, ensuring timely and budget-friendly project delivery. Fostered a positive team environment, enabling seamless coordination for efficient project execution. ACADEMIC PROJECTS

Rent A Car Platform:

• Rent-A-Car platform was developed using Lightning Web Components (LWC) in the Salesforce ecosystem. The project is a complete car rental management system that aims to improve and streamline the car rental process for both businesses and customers. Online Shopping System:

• Develop an e-commerce platform using Spring MVC and Hibernate to handle product inventory, shopping cart functionality, and payment processing.

• Design online shopping system in Java using JSPs, Servlets, and MySQL. Railway Reservation System

• Designed a scaled-down version of Indian Reservation System, allows consumers to reserve tickets to Indian metropolises online.

• Pure Java2EE architecture is used to implement the website with Oracle database. Front-end designing is performed using Bootstrap, HTML, and CSS.

Sentimental Analysis on Twitter using Multiple Languages

• Developed an effective method for predicting readers' emotions by categorizing tweets as positive, negative, or neutral based on sentiments conveyed.

• Designed using Python libraries such as Text Blob, Tweepy, NumPy, and Scikit-learn. ACHIEVEMENTS

• Certifications

Salesforce Platform Developer1

Salesforce Administration

• Completed 101 badges & 2 Superbadges with 100k+ points