PRIYANKA PANHALKAR
Meta
Fremont,CA
13
years of professional experience
Data Analyst with 8 years of cross-industry experience across biotech, tech and enterprise consulting, including roles at Meta,Google, NTT Data, and an early-stage startup. Adept at exploring complex, unstructured datasets and translating raw data into actionable insights, products, and growth strategies. Proficient in SQL, Python, Tableau, Hypothesis and A/B testing, with expertise in statistical modeling and data storytelling. Currently exploring Regression and Forecasting Models that adapt to real-world change,capturing signal through uncertainty. A collaborative, impact-focused problem solver known for driving innovation and cross-functional outcomes at scale. Proficient in data storytelling that drives alignment and trusted cross-functional partnerships across Product, Eng, and DS.
Work History
Data Scientist
7 Months- Diagnosed and resolved failures in large-scale data and ML pipelines, improving reliability and reducing downtime for privacy compliance workflows.
- Analyzed privacy risk detection and automated test generation models, providing feedback to enhance model accuracy and reduce false positives by cross functional collaboration to interpret model outputs, prioritize fixes, and drive continuous improvement in safeguards.
- Validated the effectiveness of ACH-generated tests in hardening code against privacy regressions and catching privacy-related bugs prior to production.
- Drove a measurable 5% reduction in privacy-related SEVs (Severity incidents) by strengthening integration between risk detection models, automated compliance hardening systems, and regression testing frameworks.
- Defined success metrics and measurement strategies for privacy workflows.
- Improved mean time to detect (MTTD) from 3 hours
- 47 minutes through near-real-time streaming anomaly detection, catching 94% of privacy incidents before production impact.
- Prepared and presented timely performance reports to senior leadership, highlighting key results (KRs), model efficacy metrics and risk trends to inform strategic decisions and resource allocation.
Data Analyst
1 Year 10 Months- Led cross-functional collaborations across engineering and operations, leveraging machine learning, statistical modeling, cloud testing, and workflow automation to optimize efficiency, enhance decision-making, and ensure seamless service delivery in Google Cloud.
- Optimized backend SQL data models, enhancing data integrity and availability, leading to 50% faster query performance for dashboard users.
- Led cross-functional analytics initiatives, transforming raw SQL and ETL data streams into production-grade dashboards serving 10K+ stakeholders, reducing manual reporting by 20% and accelerating insight delivery.
- Engineered and managed 5 complex ETL pipelines, conducting RCA on failures, reducing data downtime by 10%, directly supporting seamless analytics execution.
- Tested and validated large-scale data pipelines and dashboard integrations, identifying root causes of data anomalies and reducing downtime by 10% through rapid correction and schema-level modifications.
- Built and deployed 5+ production-grade Complex workflows, scaling program orchestration and lifecycle tracking, resulting in automated workflow efficiency gains of 30% and faster project execution.
- Used statistical modeling to analyze historical data and trends, enabling accurate timeline forecasting for project milestones, ensuring on-time delivery and improved execution efficiency.
Data Science Fellow
1 Year 7 Months- Develop end-to-end data science solutions by building scalable pipelines, uncovering insights through EDA, and deploying advanced machine learning models and dashboards to drive informed business decisions. As a Data Scientist, I have hands-on experience leveraging Hadoop for distributed data processing, using Amazon S3 as a scalable data lake to store and manage structured and semi-structured datasets, and utilizing Presto for performing fast, SQL-based exploratory analysis across large-scale data sources. Managed all phases of experimental projects, from hypothesis generation to data analysis and reporting, ensuring adherence to best practices and delivering valuable insights to stakeholders.
- Streamline complex data workflows by collecting, cleaning, transforming, and merging structured and unstructured datasets using Python, ensuring high-quality, scalable data pipelines for analysis and modeling.
- Uncover actionable insights through statistical summaries and visualization techniques, enabling feature engineering and optimized model development for predictive analytics.
- Enhance data integrity and decision-making with exploratory data analysis, statistical methods, and outlier detection, ensuring robust, bias-free models and high-quality analytics for critical applications.
Lead Data Analyst
1 Year 2 Months- Led cross-functional Tableau dashboard migration and pipeline optimization, enhancing trend forecasting accuracy, stakeholder collaboration, and data-driven decision-making efficiency.
- Designed and deployed Tableau dashboard development at NTT Data, integrating real-time pipelines and time series forecasting to support critical workplace decisions across operations and service lines.
- Led the migration of legacy systems to a new Python-based platform, resulting in a 30% reduction in server response times and increased system stability.
- Modified existing enterprise data models to support new analytics use cases in workplace and real estate domains, working closely with backend engineers and IT stakeholders.
- Conducted deep-dive retention analysis A/B testing initiatives to evaluate design variants, optimize feature rollouts, and quantify user behavior impact; insights led to a 15% improvement in feature adoption and reduced bounce rates.
- Delivered successful data migration initiatives, maintaining 100% adherence to scope and timeline through agile methodologies, improving stakeholder satisfaction and analytics adoption rates.
- Led stakeholder engagement and business insights presentations, transforming complex datasets into actionable intelligence, enabling leadership to make data-driven decisions with increased efficiency.
- Acted as the primary analytics liaison between data engineering teams and Fortune 500 clients, resulting in 25% fewer reporting discrepancies and increased stakeholder trust.
Data Analyst
10 Months- Led data-driven process optimization and cost-reduction initiatives by analyzing POS, sales, and inventory data using Python (Pandas, NumPy, Matplotlib) — resulting in a 15% reduction in waste and improved production efficiency.
- Conducted A/B testing and customer feedback experiments leveraging Python (SciPy, statsmodels) to optimize formulations and application interface elements (e.g., call-to-action buttons), leading to a 12% increase in order conversion rates and an 18% uplift in customer satisfaction.
- Partnered with cross-functional teams to streamline supply chain operations, improve vendor management, and enhance workflow efficiency, contributing to measurable gains in product consistency and compliance.
- Led scientific hypothesis-driven experimentation for analyzing customer behaviour, using statistical validation and ML modeling to explore strategic business questions and product-market fit.
- Conducted deep customer and behavioral analysis using clickstream tracking and user logs; analyzed customer engagement patterns to understand how users interact with ordering interface and product features.
- Designed and executed feedback-driven experiments that optimized customer experience and boosted net promoter scores (NPS) in a fast-paced startup environment.
- Built behavioral cohorts from user logs to segment customers by engagement level and purchase patterns; used cohort analysis to identify high-value users and optimize marketing spend.
Quality Analyst
10 Months- Managed and standardized product specifications using structured data; maintained supplier compliance data pipelines; analyzed customer feedback and quality metrics; led process improvement initiatives; and utilized Salesforce CRM for DM and reporting.
- Managing complex case lifecycles—tracking status updates, ensuring timely resolution, and maintaining audit-ready documentation across cross-functional workflows.
Quality Specialist
1 Year 6 Months- Applied statistical process control (SPC) to monitor product quality, implemented critical control points using data-driven decisions, managed product and ingredient databases, automated quality workflows in ERP-SAP, and supported data documentation, training, and anomaly resolution across manufacturing operations.
Education
Master of Science - Food Technology
GPA: 3.8
Bachelor of Engineering - Biotechnology
GPA: 3.75
Skills
Programming: Python (NumPy
Pandas
Scikit-Learn
TensorFlow
PyTorch
Statsmodel)
SQL (Advanced)
HTML
Statistical Methods: Descriptive & Inferential Statistics
Hypothesis Testing
Precision
Recall
ROC curve
Data Normalization
Concepts & Methodologies: Data Cleaning / Data Wrangling
Feature Engineering
Regression / Classification / Clustering
Experimentation: A/B Testing
Causal Inference
Power Analysis
Holdout Design
Incrementality
Product DS: Metrics Design
North Star Metrics
Guardrail Metrics
Funnel Analysis
Cohort Analysis
Retention
LTV Modeling
Scale: PySpark
BigQuery
Airflow
dbt
Data Modeling
Anomaly detection
Modern ML: LLM Evaluation
RAG
Prompt Engineering
Embeddings
Vector Databases
Comms: Data Storytelling
Executive Communication
Stakeholder Management
Timeline
Data Scientist
Meta
2025.10 - 2026.05Read More
Data Science Fellow
Springboard
2024.02 - 2025.09Read More
Data Analyst
Google
2022.03 - 2024.01Read More
Lead Data Analyst
NTT Data
2021.08 - 2022.10Read More
Data Analyst
Zume Pizza (Startup)
2018.08 - 2019.06Read More
Quality Analyst
Pacific Cheese
2017.08 - 2018.06Read More
Quality Specialist
General Mills
2013.07 - 2015.01Read More
Mississippi State University
Master of Science from Food Technology
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University of Pune
Bachelor of Engineering from Biotechnology
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