Paresh Subedi, data scientist and AI/ML engineer
diffusion denoising · t = 1000 → 0
Open to Data & Analytics, ML Engineering and AI Systems roles.
model card
Paresh-v2026
- Model
- Paresh-v2026
- Architecture
- Data Scientist + Systems Thinker
- Training data
- M.S. Data Science (Fordham), research in efficient Transformers, two years of ERP and analytics operations
- Intended use
- Analytics, ML engineering, AI product
- Known limitations
- will over-engineer a dashboard if left unsupervised
Graduate Research Assistant at Fordham University, researching neuroscience-inspired ways to make Transformer-based LLMs faster and more energy-efficient through inhibitory mechanisms and sparse activation. Before that, two years at Genpact in Bangalore managing SAP ERP accounts and building the Tableau reporting behind them.
85%
Validation accuracy
CNN ensemble on HAM10000
1.3M
Rows engineered
A decade of daily S&P 500 data
10%
Top of cohort
Merit scholarship, Jain University
education
- M.S. Data Science · Fordham University
- B.Tech (Honours), Computer Science, Data Science · Jain University
layer 02 · embedding space
The Embedding Galaxy
Each cluster is a project. Hover to expand one, click to fly inside. Colour carries meaning: cyan = data, magenta = learning, amber = output.
layer 03 · optimisation
The Loss Landscape
Each skill group is a valley, and deeper means stronger. Scroll and the ball rolls down into the next one.
01Python
depth 95%- Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
02SQL
depth 85%- SQL
- NoSQL
- Tableau
- Power BI
03ML
depth 85%- Scikit-learn
- XGBoost
- Feature engineering
04Deep Learning
depth 80%- PyTorch
- TensorFlow
- Keras
- CNN ensembles
05NLP
depth 70%- Hugging Face
- Embeddings
- Moral Integrity Corpus
06LLMs & Agents
depth 75%- CrewAI
- Multi-agent systems
- RAG
- Transformers
07Cloud & MLOps
depth 55%- Git
- Streamlit
- PySpark
- HDFS
- MapReduce
08Data Viz
depth 90%- Tableau
- Power BI
- Matplotlib
- Seaborn
09Systems Architecture
depth 65%- SAP
- Salesforce
- Pega
- Bash
layer 04 · training log
Experience
$ python train.py --career --epochs 2
epoch 1/2 · 2025 — Present
Graduate Research Assistant
Fordham University · New York, USA
- >Researching neuroscience-inspired methods to improve the energy efficiency and inference speed of Transformer-based LLMs, under faculty supervision.
- >Exploring inhibitory mechanisms and sparse activation to cut redundant computation in large-scale neural networks.
epoch 2/2 · 2023 — 2025
Senior Associate
Genpact · Bangalore, India
- >Onboarded and maintained customer accounts in SAP ERP systems, keeping data entry accurate and timely.
- >Resolved account discrepancies with cross-functional teams, reducing data errors and improving customer experience.
- >Built Tableau reports on customer account metrics that surfaced patterns improving operational efficiency.
- in production operations
- 2 yrs
checkpoints
M.S. Data Science
Fordham University · 2025 — Present
Graduate Research Assistant and Graduate Assistantship recipient.
B.Tech (Honours), Computer Science, Data Science
Jain University · 2019 — 2023
Coursework in Python, data analytics, machine learning, deep learning and NLP. Best Final-Year Project in deep learning for dermatology.