Data Science Professional
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Assessing your cultural and operational fit
WildGuard
April 17, 2026 – Present
Offline Android outdoor companion — UV safety, weather forecasting, altimetry, celestial computation, tide prediction, compass navigation, and thermal risk — all without internet connectivity. Pure algorithmic computation, no ML, no cloud.
View Projectsolguard
April 10, 2026 – Present
Offline UV index estimator & sun safety timer for Android. Uses phone sensors, no internet needed.
View Projecttwin-delayed-ddpg-card
January 16, 2026 – Present
Autonomous car navigation using TD3 (Twin Delayed DDPG) with continuous steering control and multi-target pathfinding
View ProjectRL-Assignment-Solutions
January 6, 2026 – Present
RL Assignments: Value Iteration (GridWorld) & DQN Autonomous Car 🔹 Assignment 1: Value Iteration on 4x4 GridWorld 🔹 Assignment 2: DQN-based self-driving car with custom maps, sequential targets, and safety systems Features: Ray-casting sensors, prioritized replay, adaptive exploration
View Projectdeepseek-v3-mlha-moe-shakespeare
December 31, 2025 – Present
A from-scratch implementation of DeepSeek-V3 architecture with Multi-Latent Head Attention (MLHA) and Mixture of Experts (MoE), trained on Shakespeare text. Features loss-less load balancing and INT8 quantization for HuggingFace Spaces deployment
View Projectsmollm2-shakespeare-training
December 27, 2025 – Present
SmolLM2-135M: Modern Llama-style transformer with RoPE, RMSNorm, GQA, and SwiGLU trained on Shakespeare
View ProjectGPT-2-Shakespeare-Generator
December 26, 2025 – Present
GPT2 architecture trained on small Shakespeare data
View Projectmarathi_tokenizer
November 10, 2025 – November 10, 2025
marathi_tokenizer — GitHub repository
View ProjectResNet50_ImageNet1k
October 24, 2025 – November 6, 2025
ResNet50_ImageNet1k — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards personal, research-oriented ML/DL projects. While demonstrating strong technical curiosity and self-learning, there is no evidence of collaborative team projects, open-source contributions, or experience in a professional team environment. This might indicate a potential gap in cultural fit for roles requiring significant teamwork and cross-functional collaboration. The projects align well with a research-heavy Data Scientist role but less so with a product-focused one.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a strong independent work ethic and initiative in exploring advanced technical topics.