نبذة عني
Data Scientist with 1.5 years of experience developing and deploying high-accuracy Machine Learning, Deep Learning, NLP, and Generative AI solutions. Proven track record of achieving up to 95% model accuracy, improving p…
Data Scientist with 1.5 years of experience developing and deploying high-accuracy Machine Learning, Deep Learning, NLP, and Generative AI solutions. Proven track record of achieving up to 95% model accuracy, improving performance by 20–30%, and building production-ready AI systems using Python, TensorFlow, Keras, Scikit-learn, Tableau, and Hugging Face. Strong background in data preprocessing, statistical modeling, forecasting, and visualization, with the ability to present insights that accelerate decision-making and drive measurable business impact. Passionate about scalable AI, real-world problem solving, and continuous innovation.
الخبرة
Data Scientist
<p>Data Scientist – Solitaire International LLP, Hyderabad (2024 – 2025)</p><p></p><p>Performed data extraction, cleaning, and transformation using Python (Pandas, NumPy), ensuring high quality datasets for analysis and modeling.</p><p></p><p>Built interactive dashboards and KPI reports in Tableau, enabling management to track business performance and make data driven decisions.</p><p></p><p>Conducted statistical analysis including correlation studies, hypothesis testing, regression models, and trend forecasting to identify actionable insights.</p><p></p><p>Presented analytical insights, dashboards, and performance reports directly to the Head of Operations and CEO, supporting strategic planning and faster decision making.</p><p></p><p>Implemented best practices in data validation, governance, and version control to ensure accuracy, consistency, and reliability across all data projects.</p><p></p><p>Performed data extraction, cleaning, and transformation using Python (Pandas, NumPy), Ensured high data quality and consistency for analysis.</p>
Data Science Intern
<p>NullClass – Data Science Intern (Hyderabad, 2024)</p><p></p><p>Developed and trained CNN models for facial emotion detection using TensorFlow and Keras, improving accuracy through data augmentation and hyperparameter tuning.</p><p></p><p>Built an age and gender detection system using OpenCV and Keras, ensuring consistent performance across diverse image datasets.</p><p></p><p>Enhanced model robustness by applying regularization, feature extraction, and optimization techniques for real world reliability.</p><p></p><p>Designed a user friendly GUI for AI models, improving usability and accessibility for nontechnical users.</p><p></p><p>Worked on preprocessing, dataset structuring, and evaluation metrics to ensure high quality, production ready model outputs.</p>
Data Scientist
Data Science Intern
<p>Performed data extraction, cleaning, and transformation using Python (Pandas, NumPy), ensuring high data quality and consistency for analysis.<br>
Utilized Tableau Desktop to develop interactive dashboards, KPIs, and visual reports, enabling business stakeholders to monitor key metrics and make data driven decisions.<br>
Conducted statistical analysis including correlation analysis, hypothesis testing, regression models, and trend forecasting to uncover actionable business insights.<br>
Presented analytical reports and dashboards directly to the Head of Operations and CEO, ensuring the data was accurate, insightful, and aligned with strategic decision-making needs.<br>
Ensured data governance and accuracy by applying best practices in data validation, cleaning, and version control.<br>
Developed and trained a Convolutional Neural Network (CNN) for image classification using TensorFlow and Keras.<br>
Utilized ImageDataGenerator for data augmentation and preprocessing of grayscale images.<br>
Improved model accuracy by fine-tuning hyperparameters and implementing regularization techniques, ensuring robust performance on unseen real-world images.<br>
Developed an advanced graphical user interface to classify the age and gender of a person based on a photograph using OpenCV and Keras.<br>
Improved model reliability across varied datasets, ensuring consistent real-world performance.</p>