AK01GET IN TOUCH
COSMIC SECTOR: 01

Can datashapehow wePREDICT?

Arjun Khanna portrait
  • DATA SCIENTIST
  • AI SYSTEM ARCHITECT
  • APPLIED ML ENGINEER
  • CO-FOUNDER @ FLYING SAPPHIRE
  • PYTHON
  • SCIKIT-LEARN
  • PYTORCH
  • SQL / T-SQL
  • FASTAPI
  • MLFLOW
  • POWER BI

THE PROOF

“Translating multi-dimensional complexity into decisive, high-precision intelligence.”
PYTHON•SCIKIT-LEARN•PYTORCH•SQL / T-SQL•FASTAPI•MLFLOW•PYTHON•SCIKIT-LEARN•PYTORCH•SQL / T-SQL•FASTAPI•MLFLOW•

CHAPTER II — SPACES & VENTURES

Where algorithmsbecomenarrative

AGENTIC AI01

Flying Sapphire

AGENTIC AI WEB BROWSER — CO-FOUNDER & AI WORKFLOW ARCHITECT

Engineered local LLM reasoning loops and 40+ enterprise API routing pipelines (Slack, Google Workspace).

DATA SCIENCE02

GRID

DATA SCIENTIST — AMRITSAR, INDIA

Automated Python/Pandas ETL pipelines, reducing 5 hours/week manual overhead; structured enterprise SQL.

CHAPTER III — RIGOR, HONOURS & IMPACT

Rigor,honours& impact

MQF LEVEL 6 / EQF LEVEL 6

Bachelor of Science (Honours) in Applied Data Sciences — MQF / EQF Level 6 — MCAST, Malta

  • 1st1st Place / Winner: Cyber Attack Prevention & Digital Forensics Competition — GNDU, 2025
  • 1st1st Place / Winner: National Web Hack Competition — DAV College, 2024
  • 100%Perfect Benchmark: Wine Quality Predictive ML Pipeline & Statistical A/B Testing Suite

SPECIALIZATIONS

Data Governance & Security · Statistical Hypothesis Testing · MLOps Lifecycles

CHAPTER IV — SHAPING MODELS & LOGIC

Shapingmodels& logic

01

Sports Odds Predictor & Anomaly Detection Pipeline

End-to-end ML model built with Scikit-learn, MLflow, and T-SQL to detect high-risk betting anomalies and simulate automated fraud mitigation in real time.

02

Automatic Credit Card Approval Engine

High-precision classification on highly unbalanced financial datasets, systematically optimized via GridSearchCV hyperparameter tuning to eliminate false positives.

03

Chemical & Quality A/B Testing Engine

Rigorous statistical hypothesis testing, t-Tests, and multi-format ETL parser (CSV/JSON).

CHAPTER V — SCALE & METRICS

0+

Enterprise APIs routed autonomously

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Benchmark score on statistical experiment lifecycles

0+ Hrs

Weekly enterprise pipeline overhead eliminated per workflow

C2

Proficient mastery in English technical communication