Aspiring ML Engineer - Data Science Fresher

Bali Tarun Teja

**************@*****.*** https://www.linkedin.com/in/tarun-teja-bali-741713211 +91-939******* SUMMARY

Aspiring Machine Learning Engineer with a strong foundation in machine learning and deep learning, supported by a Dual Degree from IIT Bhubaneswar.

Skilled in predictive modeling, Exploratory data analysis, and building end-to-end ML pipelines using Python. Passionate about uncovering insights from data and developing AI-driven solutions to solve real-world problems. SKILLS & INTERESTS

Programming :

Language

Python

OS & :

Tools

Windows, Linux, Jupyter Notebook,Google Colab, VS Code DataBase : Microsoft SQL Server

Data :

Analysis/Visualization

Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Power BI Machine :

Learning

Regression, Classification, Supervised/Unsupervised Learning, Ensemble Methods (XGBoost, Random Forest, AdaBoost), Model Evaluation, Hyperparameter Tuning Deep :

Learning

ANN, CNN, RNN, GANs (basics), Model Training, SHAP, PDP (model interpretation) Interests : Exploring ML/AI Trends, Reading Fiction Novels EDUCATION

IIT BHUBANESWAR Jatni,Odisha

B.Tech-M.Tech(Dual Degree)-Civil Engineering Graduation Date: Jun 2025 ACADEMIC PROJECT EXPERIENCE

Indian Institute of Technology, Bhubaneswar Argul - Jatni Rd, Odisha Effect of Sulphate attack on RCA using ML& DL Jan 2025 - Jul 2025 Used Machine Learning and Deep Learning models like XGBoost, Adaboost, Random Forest, ANN& 1D-CNN for predicting the compressive strength, mass loss, and water absorption of recycled concrete aggregates. Used GANs (Generative Adversarial Networks) for generating new data instances that resemble the training data. Improved model accuracy by 15% using grid and random search for hyperparameter tuning. Performed SHAP and PDP analysis for feature importance, showcasing the most important features. Prediction of CS& WA of RCA using ML models Jul 2024 - Nov 2024 Developed and deployed supervised ML and DL models (Random Forest, XGBoost, ANN, CNN) to predict key performance parameters in material datasets. Improved model prediction accuracy by 12% with advanced hyperparameter tuning (grid/random search).

Utilized SHAP and Partial Dependence Plots for model interpretability and key feature identification. CERTIFICATIONS

Certifications : Executive PG Certification in AI & Machine Learning, IIT Roorkee (Mar 2025 - Present)

Data Science Training, Internshala (Jun 2022 - Aug 2022) Machine Learning Training, Internshala (Jun 2022 - Aug 2022) IBM Skill Build: Artificial Intelligence Fundamentals (In Progress) ADDITIONAL INFORMATION

Languages: English, Telugu, Hindi

Soft Skills: Proactive, detail-oriented, collaborative team player, quick learner with high adaptability

Contact this candidate