Top-Tier Data Scientist | ML & Deep Learning Expert | Power BI | Python/SQL | Data Engineering & Analysis
Full-Stack Data Solutions | DS • DA • DE • ML • DL | Enterprise Quality for Premium Clients
Need expert-level support in Data Science, Engineering, or Analysis? You're in the right place.
I’m a seasoned data professional who handles the entire data pipeline, from raw extraction and engineering to advanced Machine Learning and interactive visualization. My stack includes Python, SQL, Power BI, TensorFlow, spaCy, and other enterprise-grade tools.
Whether you're launching a product, building dashboards, training ML models, or cleaning complex datasets from multiple sources — I offer results that deliver true business value.
What I Deliver: Data Analysis & Business Insights
Data wrangling, EDA, trend discovery
Power BI dashboards for decision-makers
Automations for recurring reports & alerts
Data Engineering
Normalization of messy/duplicate records across data sources
ETL pipelines for structured data flows
Seamless integration of APIs, JSON, CSV, Excel, MySQL
Machine Learning & Deep Learning
Classification, regression, clustering models
NLP with spaCy (keyword extraction, sentiment analysis, topic modeling)
Deep Learning: CNNs, RNNs, LSTMs using TensorFlow & Keras
Deployment-ready ML code with metrics and reports
Tech Stack / Tools:
Languages: Python, SQL
ML/DL: Scikit-learn, TensorFlow, Keras, PyTorch, OpenCV
NLP: spaCy, NLTK
Visualization: Power BI, Matplotlib, Seaborn
Data Tools: Pandas, NumPy, Jupyter, Git
Data Sources: MySQL, Excel, CSV, APIs, JSON
Highlighted Projects:
- Duplicate Record Normalization & Integration
Engineered a smart system in Python to clean and merge datasets from multiple sources. Applied fuzzy matching & normalization techniques to eliminate duplicate entries and standardize formats for unified analytics.
- Text Keyword Research Using ML & Python (NLP)
Developed an NLP pipeline using spaCy and ML algorithms to extract and rank keywords from product reviews and research articles. Helped a client improve SEO and content targeting through data-driven keyword clusters.
- Iris Flower Classification – 100% Accuracy Achieved
Built a Logistic Regression model to classify Iris flower species using scikit-learn. Delivered 100% accuracy and visualizations including correlation matrix, pair plots, and feature histograms.GitHub Repo: Dineshyalamaddi/Iris-Flower-Classification
Why Choose Me?
- Master of DA + DE + DS + ML + DL
- Fluent in both Business Impact & Technical Execution
- Portfolio of real, working projects
- Clean, modular, well-documented code
- Clear communication + On-time delivery = Your peace of mind
Let’s Build Something Powerful
You bring the data or the idea—I’ll bring the insights, pipelines, intelligence, and results. Message me now and let’s make your project a success.