Looking for a job

Kendra Obika

@kendraobika

Message

Data Scientist at Nasdaq who cut manual review time by 70% with an entity resolution system.

United States

Message

At Nasdaq, I architected Databricks ML pipelines and developed an entity resolution system that reduced manual review time by about 70%. I also automated data-cleaning workflows, eliminating more than 150 hours of monthly manual work across two internal teams.

At RevealMe, I architected a privacy-first LLM-powered knowledge graph and developed hybrid graph and vector retrieval methods, improving retrieval precision by about 35%. I also led development of an end-to-end ML system for entity extraction and embedding generation, reducing memory processing latency by about 50%.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Nasdaq

Feb 2023 - Present (3 years 9 months)

Architected Databricks ML pipelines and developed a classification-based entity resolution system, reducing manual review time by ~70%. Engineered AWS-backed workflow automation and deployed a production ML system for automated Salesforce case resolution.

Databricks Spark SQL AWS Lambda Appsmith Salesforce Classification Entity Resolution ML Pipelines Automation

Lead Data Scientist (Part-Time)

RevealMe

Jul 2025 - Feb 2026 (7 months)

Architected a privacy-first LLM-powered knowledge graph using Neo4j and pgvector, improving retrieval precision by ~35%. Developed a graph-based relevance ranking model and led development of an end-to-end ML system for entity extraction and embedding generation.

LLM Neo4j Pgvector Graph Databases Vector Search Entity Extraction Embeddings Retrieval Ranking ML Systems

Education

Degrees, certifications, and relevant coursework

University of Texas at Austin

Master of Science, Data Science

Grade: 4.0/4.0

Pursuing a Master of Science in Data Science with an expected graduation in May 2027. Coursework includes machine learning, natural language processing, and advanced deep learning.