# Lokranjan P — Professional profile

Data Scientist I at MiQ Digital | Bengaluru, India
Turning data into systems that do something useful.
I build production ML and agentic AI systems. From semantic retrieval to intelligent workflows, I like taking an idea all the way from experiment to something people can use.

## Experience
### Data Scientist I — MiQ Digital
JAN 2025 — PRESENT | Bengaluru, India
- Agentic audience workflows: Built a real-time agentic workflow that turns trader queries and first-party data into custom audiences with R-F-D scores. Integrated data APIs and tools to give the agent relevant, high-quality context.
- MLOps, with less overhead: Productionized automated data refresh and onboarding pipelines. Used Amazon Bedrock Batch Inference to reduce monthly LLM token costs by 70% and remove the LangChain dependency from the pipeline.
- From creatives to audiences: Orchestrated an image/video-to-metadata pipeline that normalizes ad creatives and maps them to IAB categories, cutting traders’ manual audience selection time by 50%.
- Smaller models, faster relevance: Fine-tuned a MiniLM cross-encoder with soft labels from a RoBERTa model, evaluated it with NDCG and MSE, and packaged it in MLflow. Reduced computation time by 40%.
Technologies: Python, PySpark, AWS Bedrock, LangGraph, MLflow, Databricks

## Measurable impact
- 70% lower LLM token costs — Bedrock batch inference
- 50% less manual selection time — Creative-to-audience pipeline
- 40% less computation time — Cross-encoder fine-tuning

## Projects
### Garmin MCP
DEC 2025 — FEB 2026
A personal fitness intelligence layer. Connect Garmin data to AI tools, understand the patterns, and get useful insights delivered to your inbox.
- Unified real-time and historical Garmin Connect data through Garth’s SSO access layer; adopted by 2,000+ users.
- 15+ analytical tools for physiological and activity metrics, statistical analysis, rolling trends, and visualizations.
- Automated daily, weekly, and monthly insight reports delivered through SMTP.
Technologies: Python, FastMCP, Garth, Statistical analysis, SMTP
Repository: https://github.com/lokranjanp/garminmcp

### AsteroidsAI
MAY — OCT 2024
Teaching an agent to survive an arcade universe. An exploration of reinforcement learning, attention, and the space between human and machine gameplay.
- Upgraded a baseline Deep Q-Network to a Transformer-Q Network with attention for multi-object tracking.
- Trained on AWS SageMaker with custom reward–penalty logic for stable Q-learning.
- Recognized as Best Minor Project at NIE in 2024, across 240 teams.
Technologies: Python, PyTorch, Pygame, Transformers, AWS SageMaker
Repository: https://github.com/lokranjanp/AsteroidsAI

### OnlyMemes
SIDE PROJECT
A Flask app for discovering random Reddit memes across multiple subreddits. Redis caching keeps retrieval fast and the scrolling seamless.
Technologies: Flask, Redis, Python, CSS
Repository: https://github.com/lokranjanp/OnlyMemes

## Skills
- Programming: Python, PySpark, SQL, MySQL, PostgreSQL
- Machine learning: XGBoost, scikit-learn, MLflow, Hypothesis testing
- AI & search: LangGraph, LangChain, FastMCP, Cross-encoders, Embeddings, Semantic / hybrid search
- Cloud & infrastructure: AWS S3, AWS Bedrock, AWS SageMaker, Databricks, CI/CD, Git

## Education
### The National Institute of Engineering
B.E. in Information Science | DEC 2021 — SEP 2025 | Mysuru, Karnataka
CGPA: 8.6 / 10

## Awards
- 2025–2026: Best Individual Contributor — MiQ Digital · Q4 2025 & Q2 2026. Recognized for technical enhancements and product impact.
- 2024: Best Minor Project — The National Institute of Engineering. Awarded across 240 teams for the AsteroidsAI project.

## Professional links
Portfolio: https://lokranjan.dev/
LinkedIn: https://www.linkedin.com/in/lokranjanp/
GitHub: https://github.com/lokranjanp
Company: https://www.wearemiq.com/
Résumé: https://lokranjan.dev/resume.pdf
Plain-text profile: https://lokranjan.dev/llms.txt