Predictive Modeling and Statistical Forecasting Expert

ANUSHKA SAHA

*******.****@*******.*** 732-***-**** www.linkedin.com/in/anushka-saha-472a66205 github.com/AnushkaSaha25 PROFESSIONAL SUMMARY

Ph.D. candidate with expertise in predictive modeling, advanced analytics, and statistical forecasting. Skilled in leveraging machine learning, quantitative methods, and programming for strategic insights and decision support across business, finance, and research environments.

SKILLS

Programming & Analytical Tools: Python, C, R, MATLAB, SQL, Tableau, Power BI Quantitative Methods: Regression, Classification, Clustering, Time Series Analysis (ARIMA, VAR), Stochastic Simulation, Monte Carlo, Optimization, Predictive Modeling

Machine Learning & Libraries: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Statsmodels Computational & Statistical Skills: Statistical Inference, Econometric Modeling (basic), Data Visualization, Numerical Methods Other Tools: Excel (Pivot Tables, VLOOKUP), Git, LaTeX, Jupyter, Google Colab EXPERIENCE

Poisson Log-Normal (PoLoN) Process for Count Data Prediction and Analysis PhD student Rutgers, NJ Feb 2025 - present

Designed a probabilistic modeling framework integrating Gaussian Processes with Poisson-lognormal distributions for signal extraction and predictive analysis on noisy count data, providing 95% confidence intervals.

Managed and validated large-scale datasets (e.g., Bike Rental, Higgs–Boson) to ensure data integrity and modeling precision.

Applied gradient-based optimization for hyperparameter tuning, demonstrating advanced numerical and calibration skills.

Delivered interpretable predictive insights, highlighting the ability to communicate quantitative results effectively. Computational Modeling & Simulation PhD Student Rutgers, NJ May 2024-Nov 2025

Implemented the Metropolis Monte Carlo algorithm for large-scale stochastic simulations, analogous to risk modeling and derivative pricing applications in finance.

Developed and analyzed algorithms to compute system-level quantities with high numerical accuracy and computational efficiency.

Collaborated on model validation and refinement, demonstrating teamwork in data-driven research environments. Bank Customer Churn Prediction Kaggle Project Feb 2025- April 2025

Conducted exploratory data analysis and feature engineering to enhance predictive accuracy.

Built and validated classification models (Logistic Regression, Random Forest) achieving 85.6% accuracy, demonstrating practical expertise in supervised learning and statistical modeling.

Applied unsupervised learning for customer segmentation, showing the ability to identify patterns and actionable insights. LEADERSHIP AND COMMUNICATION

Teaching Assistant & Lab Instructor Rutgers, NJ Fall 2023- Present

Simplified complex quantitative and computational concepts for undergraduates, demonstrating strong written and verbal communication skills.

Collaborated with a team of instructors to develop and deliver effective lab sessions, ensuring a consistent and high-quality learning experience.

Managed a classroom independently and provided one-on-one student mentorship, showcasing strong leadership and independent problem-solving abilities.

RELEVANT COURSES & CERTIFICATIONS

Mathematics: Linear Algebra, Probability & Statistics, Analysis, Convex & Conic Optimization (Princeton University Exchange), Nonlinear Optimization

Computation & Data Science: Algorithms & Programming, Numerical Methods, Scientific Computing, Regression & Time Series Analysis, Large Data Analysis, Machine Learning, Data Mining Physics: Quantum Computing, Quantum Mechanics, Classical Mechanics, Statistical Mechanics, Mathematical Methods in Physics Certifications: IBM Machine Learning Specialization (Coursera); Data Analysis Specialization (Coursera) EDUCATION

Rutgers University - The State University of New Jersey New Brunswick, NJ, USA Sept 2023- August 2027 (Expected) PhD Candidate in Physics and Astronomy GPA: 3.8/4.0 Indian Institute of Science Bangalore, Karnataka, India August 2018-July 2023 BSc & MSc (Research) Major in Physics GPA: 8.5/10 First Class with Distinction Julius-Maximilians-Universität Würzburg, Germany Sept 2022 – Jan 2023 Guest Scientist Experimental Physics III

AWARDS AND HONORS

Awarded NTSE and INSPIRE Scholarship (national-level merit-based awards)

Secured top 1 percentile Rank in WBJEE (2018), NEST (2018), JEE Main & Advanced (2018), and Board Exam (among 1.4M candidates).

WORKSHOPS AND SUMMER SCHOOL

Learning Theory Seminar, Hands-on Artificial Intelligence/Deep Learning (AI/DL) Tutorials for Science and Engineering

(Rutgers)

Selected for Vijyoshi National Science Camp (IISc, Bangalore) and Astrophysics Summer School (ICTS, Bangalore).

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