R
Ritika S
About
Detail
US IT Recruiter|Talent Acquisition|Technical Recuiter
Princeton, New Jersey, United States
Résumé
Jobs
verified_user
0% verified
US IT RecruiterAmpstekJul 2024 - Current (2 years 1 month)- DeveloperELGI EQUIPMENTS LIMITEDDec 2022 - Mar 2023 (4 months)Assisted in the development and maintenance of web applications using HTML, CSS, and JavaScript.Engineered a cohesive strategy with Scrum masters to integrate responsive design principles, enhancing user experience and driving a 30% boost in mobile conversions and a 20% increase in overall revenue.Conducted testing and debugging procedures to ensure the functionality and performance of web applications.Learned and applied best practices in web development, including version control using agile methodologies.Implemented a structured documentation strategy, covering API documentation, user guides, and technical specifications, resulting in improved development processes and enhanced team collaboration; drove a 30% reduction in development tim
Education
verified_user
0% verified
- Bachelor of Computer SciencePSGR Krishnammal College for WomenJan 2021 - Dec 2024 (4 years)Teached School Students how to set realistic and achievable goals.Equipping students with skills to tackle challenges effectively. Offer workshops on effective communication skills, including active listening, assertiveness, and conflict resolution, to enhance interpersonal relationships.Introduce concepts from positive psychology, such as gratitude journals, positive affirmations, and strengths-based approaches, to promote resilience and optimism.
Projects (professional or personal)
verified_user
0% verified
- PPARKINSON'S PATHOLOGY IDENTIFICATION UTILIZING SOPHISTICATED COMPUTATIONAL ALGORITHMS AND STATISTICAL ANALYTICSDeveloped a machine learning model for early detection of Parkinson's disease using [ random forest algorithm and XG Boost algorithm]. Preprocessed raw data to clean and normalize inputs for accurate analysis.Pre-processed and analyzed [dataset 197 records] to extract relevant features for predictive modelling .Achieved [97%] accuracy in earlier detection of Parkinson's Disease, demonstrating the effectiveness of the machine learning model. Improved diagnostic accuracy and efficiency, leading to early intervention and better patient outcomes.Evaluated the trained model's performance on a separate test dataset to assess its accuracy, sensitivity, specificity, and other relevant metrics.