# Ibrahim Khan

Ibrahim Khan is a remote worker on Himalayas, Applied AI Directed Study at Texas A&M University, based in United States.

Source: https://himalayas.app/@ibrahimkhan13

```text
Data Analyst Intern at CompQSoft who built semantic search over government datasets and improved retrieval relevance.
```

| Detail | Value |
| --- | --- |
| Availability | Looking for a job |
| Location | United States |
| Authorized to work in | United States |
| Salary expectations | 90k+ USD |
| Job categories | Data Analyst, Data Engineer, Machine Learning Engineer |
| Skills | Data Analysis, Data Engineering, Machine Learning, ETL Pipelines, Feature Pipelines, Data Modeling, Data Quality Validation, Model Evaluation, Statistical Analysis, Embeddings, Vector Search, LLM Integrations, Drift Monitoring, Python, SQL |
| LinkedIn | https://linkedin.com/in/ibrahim-khan- |

## About

```text
At CompQSoft, I built a semantic search system over government datasets using Sentence-BERT, Hugging Face, and nearest-neighbor vector search. I fine-tuned embedding models and evaluated retrieval relevance against similarity metrics and benchmarks.

I also built Python pipelines to clean, transform, validate, and index database records, and wrote SQL for extraction, aggregation, and data quality checks.

In my market-data project, I built an incremental lakehouse for 20 securities and trained a LightGBM volatility forecaster that beat the HAR-RV benchmark in all five out-of-sample years, with 15.5% lower QLIKE.

At Texas A&M University, I’m developing an evaluation framework for an LLM agent that updates probabilistic wildfire-ignition risk beliefs from spatiotemporal data. My work examines calibration, uncertainty quantification, and fuzzy-logic evidence fusion against ground-truth outcomes.
```

## Experience

### Applied AI Directed Study (current)

Texas A&M University. Sep 2026 - Present

```text
Developing an evaluation framework for an LLM agent that generates and updates probabilistic risk beliefs from spatiotemporal tabular data for wildfire ignition forecasting. Researching calibration, uncertainty quantification, and fuzzy-logic evidence fusion methods, and working with an LLM-driven natural-language-to-SQL pipeline.
```

Skills: LLM, Evaluation-Frameworks, Calibration, Uncertainty-Quantification, Fuzzy-Logic, SQL, XGBoost

### Data Analyst Intern

CompQSoft. Jun 2026 - Sep 2026

```text
Built a semantic search system over government datasets using Sentence-BERT and Hugging Face, and fine-tuned embedding models to improve retrieval relevance. Developed Python pipelines for data cleaning, transformation, and indexing, and wrote SQL for extraction and data quality checks.
```

Skills: Python, SQL, Sentence-BERT, Hugging-Face, Vector-Search, Data-Pipelines, Data-Quality

## Education

### Texas A&M University

Master of Science, Artificial Intelligence

```text
Pursuing a Master of Science in Artificial Intelligence with expected graduation in May 2028. Coursework includes Artificial Intelligence, Analysis of Algorithms, and Directed Study in Applied AI.
```

### The University of Texas at Austin

Bachelor of Science, Informatics - Data Science. Grade: 3.3/4.0

```text
Earned a Bachelor of Science in Informatics with a focus on Data Science in May 2025. Coursework included Database Engineering, Database Design, Software Design, and Scientific Computing.
```

## Tech stack

- Tableau
- Docker Compose
- GitHub Actions
- dbt
- PostgreSQL
- Redis
- Terraform
- Python
- MLflow
- scikit-learn
- FastAPI
- Microsoft Excel
- Docker
- SQL
- Prefect
- Azure Blob Storage
- XGBoost
- Hugging Face
- LightGBM
- DuckDB
- Microsoft Fabric
- Power BI
- Azure

To contact Ibrahim, message them from this profile with a Himalayas employer account: [Hire on Himalayas](https://himalayas.app/hire).

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