Tehreem Arbab

Application Associate

S&P Global • Tiempo completo

Jul 2024 - Present • 2 yrs 1 mo

• Developed and optimized complex SQL queries on large-scale relational databases to extract, transform, and deliver structured financial datasets to enterprise clients via Snowflake and SFTP pipelines • Built automated Python workflows for data processing, reporting, and anomaly detection, reducing manual effort by ~40% and accelerating product performance monitoring • Led end-to-end server migration of client data pipelines, transferring all upload processes with zero downtime and 100% client retention within two weeks • Conducted product audits analyzing database usage patterns and KPI trends to recommend strategic improvements and optimize technical resources • Collaborated cross-functionally with product, engineering, and client-facing teams to align data insights with product roadmap decisions

Data Science Consultant

UpStack® • Tiempo parcial

Aug 2023 - Apr 2024 • 8 mos

• Designed and deployed an AI-powered semantic search system using sentence transformer models integrated with OpenSearch for scalable product retrieval • Performed extensive EDA on product datasets, engineered features, and applied NLP techniques to improve search relevance and recommendation accuracy • Evaluated and benchmarked 5 transformer models; fine-tuned the best performer for domain-specific retrieval, improving semantic matching precision • Managed full model lifecycle: data preprocessing, training, validation, deployment, and performance monitoring using MLflow and DVC