Sharon Lal

I am a data analytics professional with 4+ years of experience blending data analysis, automation, and software development. I focus on turning complex data into reliable, auditable pipelines and actionable insights using Python, SQL, and R.

At Accenture I designed and implemented a structured data pipeline to onboard pharmaceutical material records, mapped ServiceNow inputs to SAP MDG-M schemas, and developed UiPath workflows to automate ingestion and reconciliation, improving cross-system consistency and audit readiness.

At Conduent I built Python-based duplicate invoice detection logic and automated workflows that reduced manual review time substantially; I also analyzed execution data from 40+ bots, performed EDA to identify anomalies, and built dashboards to quantify automation performance and FTE savings.

I am completing an MS in Data Analytics Engineering at Northeastern and have completed projects in machine learning classification and invoice management database design. I strive to join a team where I can build scalable data pipelines, apply ML, and deliver measurable automation impact.