
Data Scientist specializing in Quantitative Finance, RAG architectures, and Time Series Analysis.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
pulsepredict
May 18, 2026 – Present
Probabilistic multi-horizon time-series forecasting: PatchTST + TFT + Chronos-T5 + conformal prediction + MinT reconciliation + Bayesian CausalImpact
View Projectgraphpulse
May 18, 2026 – Present
Real-time streaming fraud detection on heterogeneous transaction graphs: TGN + LightGBM + Redpanda + River ADWIN + SHAP + GNNExplainer
View Projectasymflow-audio
May 15, 2026 – Present
Rank-asymmetric flow matching for raw audio waveforms (SC09) — porting AsymFlow arXiv:2605.12964 to speech
View Projectdocumind
May 14, 2026 – Present
Multimodal document RAG — ColPali vision-language retrieval + Qwen2-VL-2B QLoRA generation with citation verification. No OCR needed.
View Projectkhetsar
May 13, 2026 – Present
Multi-modal satellite Earth observation platform for Indian agriculture — MAE pretraining, U-TAE crop segmentation, yield forecasting, production MLOps
View Projectprism
May 9, 2026 – Present
PRISM: End-to-end Customer Intelligence Platform — uplift-weighted CLV NBA scorer, churn, MMM, A/B | FastAPI + Next.js 15 + NextAuth + MLflow + Docker
View Projectsahayak
May 7, 2026 – Present
Multi-agent cognitive prosthesis for mild cognitive impairment — LangGraph + LanceDB + InsightFace + Whisper + Federated Learning + Flutter
View Projectrl-market-maker
May 3, 2026 – Present
RL Market Maker on Simulated LOB: PPO + IQN + CVaR vs Avellaneda-Stoikov, GLT, CJ baselines. Hawkes order flow, transformer policy, curriculum training.
View Projectdeep-hedging-transformer
May 3, 2026 – Present
Deep Hedging with Transformer policy under Rough Bergomi volatility — MTech quant finance project
View ProjectDynamic-Graph-Portfolio
January 28, 2026 – Present
Dynamic-Graph-Portfolio — GitHub repository
View ProjectCultural Fit Analysis
The candidate demonstrates a strong passion for data science and machine learning through a diverse portfolio of personal projects. The projects cover a wide range of applications, from finance to agriculture and healthcare, indicating adaptability and a broad interest in applying data science to various challenges. This aligns well with a culture that values innovation, continuous learning, and problem-solving across different domains. However, the lack of team-based project experience or professional work experience makes it difficult to fully assess cultural fit in a collaborative team environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions suggest a strong initiative and ability to work independently on complex problems.