Data Analyst Portfolio
I have a Ph.D. in physics with expertise in theoretical modeling, computational methods, and data analysis. I have contributed to open-source frameworks like MUSES, optimizing simulations for nuclear astrophysics. Skilled in Python (Pandas, NumPy), Fortran, SQL, and data visualization (Matplotlib, Seaborn), I have extensive experience in research writing, conference presentations, and multi-disciplinary collaboration. Passionate about applying scientific and data-driven insights to solve challenges in finance and technology. Seeking a data analyst role where I can apply my expertise in quantitative analysis, computational modeling, and data visualization to drive data-driven business insights and strategic decision-making.
Skills
Technical Skills: Fortran, Python (Pandas, NumPy), C++, SQL, sbatch, bash, LaTeX, Matlab, Mathematica
Data Visualization: Excel, Matplotlib, Seaborn, gle, xmgrace, Matlab
Version Control, Editor and AI: Git, VS Code, Jupyter Notebook, Github Copilot
Education
Ph.D. in Theoretical High Energy Physics}, National Institute of Technology, Jalandhar, India (2017 - 2021)
Relevant Coursework: Advanced Computational Methods (Analytical and Numerical Calculations)
M.Sc. in Physics, Panjab University Chandigarh, India (2012 - 2014)
Relevant Coursework: Computational Laboratory in C++
B.Sc. with Computer Science, Panjab University Chandigarh, India (2009 - 2012)
Relevant Coursework: C, C++, DBMS, HTML, CSS, OS
Experience
Post Doctoral Research Associate, Kent State University Ohio US March 2022 - March 2025
Developed a module of an open-source computational framework for nuclear astrophysics simulations, enhancing research reproducibility and accessibility.
Assisted with the optimization of Chiral Mean-Field (CMF) model implementations, improving computational efficiency by four orders of magnitude, and facilitating faster simulations of dense nuclear matter at zero temperature.
Collaborated with international researchers within the MUSES and NP3M collaboration, contributing to multi-institutional projects on hot and cold nuclear equations of state.
Conducted large-scale data analysis and visualization using Python, extracting key insights from high-dimensional datasets.
Mentored graduate and undergraduate students, guiding them in scientific computing, data analysis, and theoretical modeling.
Published peer-reviewed research papers in high-impact journals, presenting findings at conferences and workshops worldwide.
Teaching Assistant, National Institute of Technology Jalandhar, India Jan 2017 - Oct 2021
Taught an M.Sc. computational lab, guiding students in Fortran programming to solve numerical physics problems and visualize results using Gnuplot.
Projects
Developed an open-source computational framework for nuclear astrophysics simulations under the Modular Unified Solver Equation of State (MUSES) collaboration.
Developing a stock market prediction model using Python, Scikit-Learn, and LSTM neural networks to forecast trends based on historical data.
Currently exploring the application of machine learning and Bayesian inference to predict the best nuclear equation of state for neutron stars, aiming to refine theoretical models in alignment with astrophysical constraints.
Extra-Curricular Activities
Leadership
Former President of the Physical Science Society at NIT Jalandhar, organizing quizzes, expert talks, seminars, courses, educational trips, sports meets, documentary videos, and website development for the department.
Certifications
Machine Learning with Python – Coursera 2025
Data Science Foundations – IBM 2025
Pursuing Google Data Analytics Professional Certificate, focusing on SQL and data visualization - Google