Tanisha Dhopeshwar

Data scientist who turns messy data into clean datasets, reliable metrics, and models people can act on, across SQL and ETL pipelines, statistical analysis, predictive modeling, and stakeholder reporting.

Technical AI Research Associate at Keywords Studios (Amazon Nova Act) (2025-07 – 2026-08)

Owned evaluation data, quality metrics, and failure analysis for Amazon's production web automation agent.

• Analyzed 1,000+ agent interaction logs and categorized them into a failure taxonomy of 150+ documented cases, giving engineering a prioritized fix list that improved issue resolution by 35%.
• Defined measurable success criteria for 60+ task types and implemented them as automated verifier code, replacing subjective review with reproducible pass/fail labels.
• Found a measurement flaw where outcome-only checks recorded false passes when the agent skipped a required step, and fixed the metric to validate intermediate actions as well as end states.
• Monitored label quality across 500+ weekly interactions, leading a 5 person annotation team through spot checks and calibration syncs to keep reviewer judgments consistent.
• Built ground truth datasets from 250+ structured prompts and rubric based scoring criteria, improving model response accuracy by 18%.

Machine Learning Scientist at EntreVita Inc. (2024-07 – 2024-12)

Built and deployed predictive models for an AI precision nutrition product, from prototype to production.

• Built a YOLOv5 and MiDaS pipeline estimating real world height from a single image, validated at 96% detection accuracy on labeled test sets.
• Fine tuned LLMs with QLoRA for a dietician recommendation pipeline, improving nutrient match relevance by 22%.
• Containerized and deployed inference services with Docker on Azure, cutting serving latency by 40% while holding 99% uptime.

Senior Executive (Data Engineering) at Vodafone Intelligent Solutions (2021-08 – 2023-03)

Promoted from Graduate Engineer Trainee in Aug 2022. Built data pipelines and models feeding business reporting.

• Built a GCP pipeline moving raw data through Cloud Storage and Vertex AI into BigQuery, delivering analysis ready tables to downstream reporting teams.
• Built ML based anomaly detection that flagged data quality issues before they reached stakeholder facing reports, and automated recurring ETL jobs, improving data quality metrics by 37%.
• Shipped a TensorFlow personalization model that increased customer engagement by 27%.

M.S. in Data Science – San Jose State University (2025-05)

B.Tech in Electronics and Communication – MIT World Peace University (2021-05)