Where I'm headed
Deepali transitioned from fundamental physics research to applied data science, leveraging 12+ years of expertise in analyzing massive datasets and building ML pipelines. She combines rigorous scientific methodology with modern ML/DL techniques to solve complex real-world problems in healthcare, finance, and sustainability.
Targeting
- AI Engineer
- Data Scientist
- Machine Learning Engineer
- Research Scientist
- Senior Data Analyst
What I bring
- ›Large-scale data processing and analysis (terabytes to petabytes)
- ›Machine learning & deep learning model development (Scikit-learn, Keras, XGBoost, LSTM, CNN)
- ›Scientific computing and statistical analysis with rigorous methodology
- ›Data pipeline architecture (Bash, Perl, C++, SQL) on HPC clusters
- ›Cross-functional collaboration and mentorship in complex technical environments
Proof
Cosmic Muon Monitoring System
Built automated daily monitoring pipeline (cron-based) predicting solar activity and space weather across multiple detector locations
Jefferson Lab RICH Detector Analysis
Processed terabytes of experimental data using HPC clusters; published results in leading peer-reviewed journal
ML Classification Projects
Delivered multiclass classification models (Random Forest, XGBoost) and CNN-based image classification achieving high recall metrics
PHENIX Experiment Data Analysis
Analyzed petabytes of heavy-ion collision data; published as primary author in leading physics journals
Role fit
- Data Engineer · Mid
- Data Scientist · Senior
- Machine Learning Engineer · Senior
- Analytics Engineer · Senior