Applied Mathematics Graduate · SciPy Open-Source Contributor | Aspiring Data Analyst | Northeastern Outstanding Service Awardee | Academic Math Mentor for Underrepresented Youths
Transforming complex data into strategic insights that drive impact.
Applied mathematics graduate blending engineering precision with machine learning innovation. I build end-to-end analytical solutions, from deep learning models and predictive systems to compelling visualizations that empower education programs and guide data-driven decisions grounded in evidence.
I'm a problem-solver at heart, combining the precision of engineering with the power of mathematics to tackle real-world challenges through data. With an MS in Applied Mathematics from Northeastern University and a foundation in Civil Engineering, I bring a unique perspective to data analysis; one grounded in both rigorous mathematical theory and practical application. Today I work as a Program Analyst at Northeastern, where I clean and audit cross-institutional enrollment data for a city-funded youth employment initiative, and as a Research Assistant validating Mathieu special functions for SciPy, work that put my name in the acknowledgements of a peer-reviewed paper. My projects span detecting gravitational waves with deep learning, forecasting foreign exchange markets, analyzing climate patterns for infrastructure planning, and building production websites for real clients.
What drives me is the moment when complex data reveals its story. Whether I'm building predictive models in Python, conducting statistical analysis in R, or creating spatial visualizations with GIS, I'm constantly seeking patterns that inform better decisions. My engineering background taught me to think systematically about problems; my mathematical training gave me the tools to solve them with precision. Beyond the technical work, I'm passionate about making STEM accessible. I've mentored over 100 students, helping them discover their own analytical capabilities, an experience that's sharpened my ability to communicate complex ideas clearly and work effectively across diverse teams. Currently, I'm seeking full-time Analyst roles where analytical rigor meets practical impact in data, business, or research analytics where I can leverage my interdisciplinary expertise to drive meaningful outcomes, and I'm open to relocation across the USA. I thrive in environments that value curiosity, collaboration, and the transformative power of data-driven insights.
Let's connect if you're working on challenges that need both mathematical precision and creative problem-solving.
Graduate coursework across deep learning, applied statistics, and numerical analysis with research-driven projects that pair mathematical rigor with deployable machine learning solutions.
Built a strong foundation in structural analysis, geospatial technologies, transportation systems, and design, skills that complement data-driven modeling and decision making.
Python
R
MATLAB
SQL
C
Jupyter Notebook
TensorFlow
PyTorch
Keras
NLP
Pandas
NumPy
Scikit-learn
QGIS
Matplotlib
Seaborn
Ggplot2
Power BI
CAD
AutoCAD
STAAD PRO
Google Sheets
LaTeX
Microsoft Office SuiteOwn the data behind a city-funded youth employment initiative serving 3,000+ students across 15+ Boston schools, turning enrollment and payroll records into decisions leadership can act on.
Validate Mathieu special functions for SciPy, with contributions merged into the official open-source repository and acknowledged in a peer-reviewed academic paper.
Ran the operational and analytical backbone of a six-week STEM summer program serving 100+ underrepresented students across 15+ partner schools.
Guided 30+ undergraduates through end-to-end data analysis projects, advising on statistical method selection, feature engineering, and technical communication.
Designed and built electroniscript.com, the live production site for Personal Supercomputing Systems, a Boston vendor of reconditioned GPU servers and workstations for research computing.
Developed a deep learning system that distinguishes gravitational wave signatures inside noisy LIGO GWOSC data, making astrophysical detection reproducible for research collaborators.
Engineered a hybrid forecasting workflow for EUR/USD that combines classical statistics with deep learning to surface actionable trading signals.
Modeled how lockdown time-allocation, digital behavior, and health outcomes interact across 1,182 student survey responses to surface what actually protected wellbeing.
Holding open virtual office hours so Boston Public Schools students always have somewhere to bring a math question they're stuck on.
I volunteer in the Bridge to Calculus Zoom Question Center, a live drop-in space where students from the summer STEM program bring precalculus and calculus questions as they work through problem sets. Sessions are unscripted; students arrive with whatever is blocking them that evening, from factoring and trigonometric identities to limits, derivatives, and applications of integration.
Working one-on-one over screen share taught me to diagnose a misunderstanding quickly and rebuild the concept from the student's own reasoning rather than handing over an answer. I keep the room welcoming for students who are hesitant to ask questions in a classroom, and I track recurring sticking points so program staff know which topics need more instructional time.
The Question Center is where I see the program's impact most directly: students who start the summer unsure whether calculus is for them leave with the habit of asking for help and the confidence to keep going in STEM.
Giving back through education by supporting final-year high school students from underserved communities for two years.
Volunteered as an Academic Teacher with Make A Difference, a renowned NGO in India dedicated to empowering underprivileged children through education. For over two years, I taught advanced mathematics to final-year high school students, covering a comprehensive curriculum including Matrices, Determinants, Inverse Trigonometric Functions, Relations and Functions, Continuity and Differentiability, Applications of Derivatives, Integrals, Differential Equations, Vectors and 3-Dimensional Geometry, Linear Programming, and Probability.
My commitment extended beyond traditional teaching; I invested dedicated time and personalized effort to ensure each student not only understood complex mathematical concepts but could apply them confidently. The results spoke for themselves: all my students excelled in their academics, achieving success in their final examinations and building a strong foundation for future educational pursuits.
This experience reinforced my belief in education as a transformative tool and strengthened my ability to break down complex ideas into accessible concepts, a skill that now informs my approach to data science and analytical problem-solving. Working with MAD taught me that the greatest impact comes from meeting people where they are and empowering them with knowledge that opens doors to opportunity.
I'm always excited to explore opportunities where applied mathematics and civil engineering create measurable impact. Reach out to collaborate on research, join forces on a project, or chat about the latest in data-driven engineering.
"The best way to predict the future is to create it through engineering, data-driven insights, and mathematical precision."
