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Eshban Suleman

@eshbansuleman

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Lead Data Scientist building production AI systems—improving accuracy, cutting costs, and deploying reliably.

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What I'm looking for

I’m looking for a mission-driven role where I can lead end-to-end AI delivery—partnering with stakeholders, building evaluation/monitoring, and deploying reliable systems on AWS/GCP/Azure with clear business impact.

Data Science / AI Lead with 7+ years of experience building production AI systems for public sector and enterprise clients. I currently lead AI application development for the Qatar government (MCITxOoredoo), partnering closely with stakeholders to turn ideas into working solutions.

My strength is end-to-end delivery—data annotation collaboration, evaluation frameworks, and production deployment on AWS/GCP/Azure. I’ve driven measurable impact, including 19% accuracy improvements, $124M cost savings, and 99.9% uptime.

In my current role, I built an autonomous Dashboard Analysis AI Agent that reduced manual monitoring by 20% using real-time anomaly detection across multiple KPIs. I also deployed a SQL Data Analyst AI Agent to translate natural language into SQL with validation and executive summaries, and I designed evaluation and monitoring practices to keep latency, hallucinations, and reliability under control.

Previously, I led model development across workforce management, feature store predictive modeling, and credit scoring—building robust evaluation and continuous monitoring before deployment. Earlier, I owned ML pipelines from research to production at Foretheta, scaling semantic search to 10M+ patents and shipping production RAG and LLM systems with strong engineering rigor.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Scientist

Current

Ooredoo

Jul 2025 - Present (8 months)

Led development of MCITxOoredoo AI applications, including an Azure OpenAI + LangGraph autonomous dashboard agent that reduced manual monitoring by 20% and delivered real-time KPI anomaly detection. Implemented LLM-to-SQL automation with 1,000+ weekly queries, built multi-agent coding workflows, and achieved 99.9% system reliability while cutting deployment time from weeks to days via MLflow/DVC C

Azure OpenAI LangGraph MLOps MLFlow DVC CI CD AWS

Senior Data Scientist

TenX.ai

Apr 2023 - Jul 2025 (2 years 3 months)

Architected and deployed workforce management and predictive models, improving Pearson retrieval performance by 19.2% total (Accuracy@1) using fine-tuned bi-encoders and cross-encoder reranking. Built high-impact telecom models (e.g., 65% accuracy Age Cohort Prediction) and credit scoring solutions that achieved Gini 0.71 (18.3% above industry standard), with continuous monitoring and A/B testing

Cross Encoders A B Testing Databricks MLFlow

Senior Data Scientist

Foretheta

Apr 2019 - Mar 2023 (3 years 11 months)

Owned end-to-end ML delivery from research to production, scaling a patent semantic search system to 10M+ documents using vector databases and transformer embeddings. Improved model quality by 49% with domain fine-tuning, reduced API latency by 40% through production deployments (Flask/TensorFlow Serving/ONNX/SageMaker), and advanced LLM RAG with automated evaluations (Precision@K, NDCG, MRR) plus

Semantic Search Vector Databases RAG Evaluation Metrics (NDCG MRR)Flask Inference Serving ONNX Runtime Model Quantization