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Hello, I'm Rohith πŸ‘‹

Your Go-To Data Science Professional 

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I’m Rohith πŸ‘‹, a passionate and results-driven data scientist with a strong focus on machine learning πŸ€– and advanced analytics πŸ“Š. I am currently working as a Senior Analyst at NestlΓ© USA, where I leverage data science to drive actionable insights and optimize business processes. My expertise spans sales and marketing analytics, supply chain optimization, consumer insights, and product performance analysis πŸ”.


Previously, I worked as a Research Assistant πŸ‘¨β€πŸ”¬ in Machine Learning at Montclair State University, developing sophisticated models for malware detection in npm packages. I also contributed at BYJU'S, where I helped improve student engagement and outcomes through data-driven decision-making πŸ“ˆ. At Enercast GmbH, I applied advanced ML techniques to enhance renewable energy forecasting β˜€οΈ.


I hold a Master’s degree in Data Science from Montclair State University πŸŽ“. My technical toolkit includes Python 🐍, SQL, cloud technologies ☁️, and machine learning frameworks such as Scikit-Learn, TensorFlow, and XGBoost.


In addition to hands-on experience, I’ve earned several industry-recognized certifications that reflect my commitment to continuous learning and technical excellence:

πŸŽ“ Certifications:

  • DP-100: Azure Data Scientist Associate
  • AI-102: Azure AI Engineer Associate
  • PL-300: Power BI Data Analyst Associate
  • DP-600: Microsoft Fabric Analytics Engineer Associate 
  • DP-300: Azure Database Administrator Associate
  • DP-700: Microsoft Fabric Data Engineer Associate 
  • DP-203: Azure Data Engineer Associate
  • AI-900: Microsoft Azure AI Fundamentals
  • DP-900: Microsoft Azure Data Fundamentals


Skills:

Machine Learning & AI: Experienced in Supervised Learning (e.g., Linear & Logistic Regression, Decision Trees, Random Forests, GBM, XGBoost, LightGBM, CatBoost, SVC/SVR, CNN, RNN, LSTM, Transformer Models) and Unsupervised Learning (e.g., K-Means, Hierarchical Clustering, DBSCAN, GMM, PCA, t-SNE, LDA, UMAP, Isolation Forests, Autoencoders). Skilled in Reinforcement Learning techniques like Q-Learning, DQN, PPO, TRPO, A3C, A2C, and MCTS. Expertise in feature engineering, hyperparameter tuning, model evaluation metrics, dimensionality reduction, NLP (e.g., NLTK, spaCy, GPT-3, BERT), large language models (LLMs), and full-cycle deployment with MLflow and cloud platforms.


Data Engineering & Analysis Skills: Proficient in building and optimizing data pipelines, ETL processes, data architecture, integration, cleansing, migration, quality assurance, and governance. Knowledgeable in data security (GDPR, HIPAA), ethics, cloud data warehousing (Snowflake, BigQuery), and business intelligence tools (Tableau, Power BI, Looker). Skilled in data storytelling, mining (RapidMiner, KNIME), and creating interactive dashboards.


Technical Skills & Collaboration: Fluent in Python, R, SQL, and frameworks like Transformers, Scikit-Learn, Keras, TensorFlow, PyTorch, and ONNX. Proficient in data analysis packages (Pandas, NumPy, SciPy) and cloud platforms (AWS, GCP, Azure). Experienced in databases (MySQL, PostgreSQL, MongoDB, SQL Server), web frameworks (FastAPI, Flask), version control (Git), and data annotation tools (Labelbox). Skilled in containerization (Docker, Kubernetes), A/B testing, collaborative tools (JupyterHub, Databricks), cross-functional team collaboration, stakeholder reporting, and delivering data-driven recommendations. Familiar with big data technologies (Hadoop, Spark, Kafka), API development, and continuously advancing analytical and problem-solving abilities.