Data Scientist & Bioinformatics Resume – Master’s Degree | Deep Learning, Machine Learning, Tableau, Python, GROMACS

Data Scientist & Bioinformatics Resume – Master’s Degree | Deep Learning, Machine Learning, Tableau, Python, GROMACS

A highly motivated, detail-oriented Data Science enthusiast with a strong foundation in Bioinformatics, Machine Learning, Data Visualization, Statistics, and Deep Learning. Skilled in problem-solving with the ability to work effectively in collaborative team environments. Seeking a career that leverages knowledge and interpersonal skills to contribute to organizational growth while advancing professional development.

Technical Stack:

Data Science / Machine Learning & AI / Deep Learning:

• Python, EDA, Supervised & Unsupervised ML algorithms, Ensemble learning, ANN, CNN, NLP, RNN, ARIMA, Feature selection, Feature engineering

Python Packages and Frameworks:

• NumPy, Pandas, Scikit-Learn, Matplotlib, TensorFlow, Keras, SciPy, Flask

Mathematics for Data Science & ML:

• Statistics & Probability, Matrices, Algebra

Visualization Tools:

• Tableau, Power BI

Programming Languages:

• Python, SQL, BioPython, Shell scripting

Web Development & Cloud Deployment:

• HTML, CSS, AWS

Databases:

• MySQL Workbench

Bioinformatics Software:

• Discovery Studio Visualizer, AutoDock 4, PyMol, Schrödinger, GROMACS

Others:

• Microsoft Office, Project Management

Languages Known:

• English, Kannada, Hindi

Education:

• Master of Technology in Biotechnology

• Bachelor of Engineering in Biotechnology 

• PUC (PCMB) 

Additional Certifications:

• Postgraduate Program in Data Science and Analytics

• Extensive Program on Recombinant DNA Technology

• Understanding of Cancer Metastasis (Coursera)

• Innovation, Business Models and Entrepreneurship (NPTEL)

• Program on Computational Genomics

Extracurricular Activities:

• Elected as Sports Vice Captain in School

• Organized and led a team for an Industrial Visit to a major agricultural biotechnology company

• Master’s Thesis shortlisted for “Best Project Award for PG Students”

Capstone Projects:

Project 1: Detection of Pulmonary Infection using Deep Convolutional Neural Network

• Developed a deep learning image classification model using ResNet50 (transfer learning) to detect pneumonia from chest X-ray images with 88% model accuracy, recall (pneumonia) of 92.6%, and F1-score of 90.02%

• Designed and deployed a user-friendly web application for real-time pneumonia detection from uploaded X-ray images

Project 2: Road Accident Analysis in India

• Surveyed and analyzed road accident data to uncover key patterns, contributing factors, and high-risk regions. Collected data from official government sources

• Built an interactive dashboard using Tableau with all key statistics highlighted

• Concluded that the highest serious casualties were from two-wheelers and the highest fatal casualties from four-wheelers

• Inferred that night-time accidents contribute the most to serious casualties

Project 3: Real Estate Market Analysis – Washington House Sales

• Analyzed housing market data to identify key factors influencing property prices and uncover trends impacting real estate decisions over time

• Developed an interactive dashboard using Tableau to visualize insights and support data-driven strategies for buyers and stakeholders

Project 4: Forecasting Stock Price using ARIMA

• Forecasted stock prices using ARIMA (SARIMAX) model, accounting for seasonality and trend in time series data

• Achieved low RMSE on training data and visualized forecast confidence intervals and trend alignment

• Optimized ARIMA parameters using grid search; further validated model with test set and rolling forecasts

Project 5: Taxi Fare Prediction

• Evaluated a case study to predict taxi fare for a taxi ride

• Performed detailed EDA to uncover patterns, such as identifying peak ride hours and comparing average fares across different times and days

• Trained a Random Forest Regressor to predict taxi fares; improved model performance using GridSearchCV

Internships:

Research Intern – Computational Genomics Center

• Studied pore opening conformational transition of a protein using Conformational flooding (GROMACS)

• Performed GCMC simulation to study ion transport in the protein in both open and closed states

• Induced mutations and conducted quantitative estimation of ion permeation through the pore

• Investigated the effect of a drug on channel gating of the mutated protein

Trainee – Biotechnology Company

• Isolated nucleic acids (RNA and DNA) from different samples and conducted qualitative and quantitative analysis

• Examined antibiotic resistance capacity for different bacteria against various antibiotics; determined Zone of Inhibition

• Estimated protein concentration in different samples by Lowry’s method

• Surveyed protein expression in different microbial samples and determined which organism showed highest protein production

Ideal For:

• Full-time Data Scientist / Data Analyst roles

• Bioinformatics and computational biology positions

• Deep learning and machine learning projects

• Healthcare and biotechnology domains

• Remote or Bengaluru/India-based opportunities

 

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