Rima Modak
Summary
Experienced Software Developer and Data Scientist with 6+ years of expertise in creating scalable applications. Proficient in Java, Microservices, SQL, AI, ML, Deep Learning, NLP, and data engineering using Python, Scala, TensorFlow, PyTorch, and AWS.
Overview
8
8
years of professional experience
1
1
Certification
Work History
Software Developer - Data Science
SynergisticIT
06.2024 - Current
- Developed and deployed machine learning models using scikit-learn, TensorFlow, and PyTorch, achieving 95% accuracy in predictive analytics and improving model performance by 20% through data preprocessing and feature engineering techniques using Pandas, NumPy, and Matplotlib.
Software Developer Intern
Frugal Innovation Hub
01.2023 - 06.2024
- Developed a cross-platform application using Flutter, Dart and PostgreSQL.
- Designed UI mocks using Figma and enhanced UI to improve user engagement and satisfaction, increasing user retention by 95%.
Cloud Engineer Co-op Intern
Cerebrone.ai
06.2023 - 12.2023
- Developed and deployed deep learning models using Keras, TensorFlow, and PyTorch on cloud infrastructure, achieving 90% accuracy in image classification, utilizing CNN for image processing and object detection tasks, enabling the development of AI-driven image analysis and recognition systems.
Software Engineer
Ericsson
08.2016 - 08.2022
- Developed a robust microservices architecture incorporating Java, Spring Boot, RESTful APIs, Docker, and Kubernetes. Achieved a significant 15% improvement in RPA efficiency while reducing errors by 10%.
- Improved data retrieval times by 20% through development and optimization of data access layers utilizing Java, Spring Data JPA, and Hibernate. Implemented advanced algorithms to enhance the efficiency of backend processes while reducing computational complexity for critical operations.
- Implemented Redis caching strategies to optimize data retrieval, resulting in minimized latency and enhanced user experience.
- Optimized SQL queries and employed efficient indexing techniques to streamline complex database operations, resulting in significant performance gains.
- Designed and implemented RESTful APIs adhering to best practices in API security and versioning, enabling seamless integration with external systems.
- Contributed closely with cross-functional teams to define and optimize data models, ensuring they aligned with business requirements for maximum performance across services. Engaged proactively in code reviews and performance tuning sessions, fostering ongoing enhancements in system efficiency and reliability.
Education
Master of Science in Computer Science and Engineering -
Santa Clara University (SCU)
Bachelor of Technology in Computer Science and Engineering -
University of Petroleum and Energy Studies (UPES)
Skills
- Java
- Spring Boot
- RESTful APIs
- Microservices architecture
- Docker
- Kubernetes
- Spring Data JPA
- ORM tools
- OracleDB
- PostgreSQL
- AI
- ML
- Deep Learning
- NLP
- Data engineering
- Python
- Scala
- TensorFlow
- PyTorch
- AWS
- Scikit-learn
- Pandas
- NumPy
- Matplotlib
- NLTK
- SpaCy
- Stanford CoreNLP
- Tableau
- Power BI
- D3js
- RAG (Retrieve, Augment, Generate) framework
- Language models
- AI-driven content creation
- Flutter
- Dart
- Figma
- UI design
- User engagement
- AI-driven features
- Personalized content recommendations
- Cloud engineering
- Keras
- CNN
- Image processing
- Object detection
- RNN
- LSTM
- Sequence-based AI models
- Data structures and algorithms
Academic Experience
Predictive Absenteeism Modeling in the Workplace (Python, Pandas, Matplotlib, Seaborn, Scikit-learn)
Developed a sophisticated predictive model using Python, Pandas, Numpy, and the Scikit-learn using regression ML algorithm, enhanced by data visualization with Matplotlib and Seaborn for effective workforce management.
Customer Sentiment Analysis using NLP (Python, NLTK, spaCy, TensorFlow)
Developed a natural language processing (NLP) model using Python, NLTK, and spaCy to analyze customer sentiment from social media and review platforms, providing insights for business improvement.
Image Classification using Deep Learning (Python, TensorFlow, Keras, OpenCV)
Developed a deep learning model capable of accurately classifying images into various categories, attaining an impressive 95% accuracy by leveraging Python, TensorFlow, and Keras.
Time Series Forecasting using LSTM (Python, Pandas, NumPy, Matplotlib, Scikit-learn)
Developed a time series forecasting model using Python, Pandas, NumPy, and Scikit-learn for predicting stock prices. The model successfully predicted stock prices, achieving a mean absolute error of 2.5%.
Certification
- Oracle Machine Learning
- Azure Fundamentals
- CCNA: CyberSecurity Essential
- IoT Specialist
Tech Stack
Programming Language: Java, C++, JavaScript, SQL, NoSQL, GraphQL, MongoDB, Python, Scala
Tools and Frameworks: Docker, MySQL, AWS, Azure, GCP, LLM, AI, Machine Leaning, Deep Learning, TensorFlow, PyTorch, NumPy, Pandas, Seaborn, Scikit, Keras, Hadoop, Spark, Django, Node.js, Flask, Flutter, Tableau, Git, Jira, Confluence, Jenkins, Splunk, Alteryx
Accomplishments
- Top 4 finalist in the AI x Law Hackathon by Stanford 2023
- 'Galactic Problem Solver' award from NASA SpaceAPP Hackathon 2023, 2023
- Ignition Center for Jesuit Education (Santa Clara University) Grant, $1,125.00, 2024
References
References available upon request.
Timeline
Software Developer - Data Science
SynergisticIT
06.2024 - Current
Cloud Engineer Co-op Intern
Cerebrone.ai
06.2023 - 12.2023
Software Developer Intern
Frugal Innovation Hub
01.2023 - 06.2024
Software Engineer
Ericsson
08.2016 - 08.2022
Master of Science in Computer Science and Engineering -
Santa Clara University (SCU)
Bachelor of Technology in Computer Science and Engineering -
University of Petroleum and Energy Studies (UPES)
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