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Hi, I'm Niharika Patil, a Data Analytics and Engineering professional with over 2 years of experience in designing scalable ETL pipelines and building predictive models to drive impactful business decisions. I’m passionate about turning raw data into actionable insights using tools like SQL, Python, and AWS, and enjoy collaborating across teams to implement data solutions that improve operational efficiency. Currently pursuing my Master of Science in Data Analytics, Public Policy and Management at Carnegie Mellon University, I have hands-on experience in developing dashboards, automating workflows, and applying machine learning models in healthcare, finance, and social good projects. I love working at the intersection of data, technology, and business to solve real-world problems and deliver value to stakeholders.…Hi, I'm Niharika Patil, a Data Analytics and Engineering professional with over 2 years of experience in designing scalable ETL pipelines and building predictive models to drive impactful business decisions. I’m passionate about turning raw data into actionable insights using tools like SQL, Python, and AWS, and enjoy collaborating across teams to implement data solutions that improve operational efficiency. Currently pursuing my Master of Science in Data Analytics, Public Policy and Management at Carnegie Mellon University, I have hands-on experience in developing dashboards, automating workflows, and applying machine learning models in healthcare, finance, and social good projects. I love working at the intersection of data, technology, and business to solve real-world problems and deliver value to stakeholders.

Niharika Patil

Data Scientist, AI Engineer, Developer, +1

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Hi, I'm Niharika Patil, a Data Analytics and Engineering professional with over 2 years of experience in designing scalable ETL pipelines and building predictive models to drive impactful business decisions. I’m passionate about turning raw data into actionable insights using tools like SQL, Python, and AWS, and enjoy collaborating across teams to implement data solutions that improve operational efficiency. Currently pursuing my Master of Science in Data Analytics, Public Policy and Management at Carnegie Mellon University, I have hands-on experience in developing dashboards, automating workflows, and applying machine learning models in healthcare, finance, and social good projects. I love working at the intersection of data, technology, and business to solve real-world problems and deliver value to stakeholders.…Hi, I'm Niharika Patil, a Data Analytics and Engineering professional with over 2 years of experience in designing scalable ETL pipelines and building predictive models to drive impactful business decisions. I’m passionate about turning raw data into actionable insights using tools like SQL, Python, and AWS, and enjoy collaborating across teams to implement data solutions that improve operational efficiency. Currently pursuing my Master of Science in Data Analytics, Public Policy and Management at Carnegie Mellon University, I have hands-on experience in developing dashboards, automating workflows, and applying machine learning models in healthcare, finance, and social good projects. I love working at the intersection of data, technology, and business to solve real-world problems and deliver value to stakeholders.

Available to hire

Hi, I’m Niharika Patil, a Data Analytics and Engineering professional with over 2 years of experience in designing scalable ETL pipelines and building predictive models to drive impactful business decisions. I’m passionate about turning raw data into actionable insights using tools like SQL, Python, and AWS, and enjoy collaborating across teams to implement data solutions that improve operational efficiency.

Currently pursuing my Master of Science in Data Analytics, Public Policy and Management at Carnegie Mellon University, I have hands-on experience in developing dashboards, automating workflows, and applying machine learning models in healthcare, finance, and social good projects. I love working at the intersection of data, technology, and business to solve real-world problems and deliver value to stakeholders.

Skills

Experience Level

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

Software Engineer Intern (Data Science Platform) at Medicodio AI

June 30, 2025 - July 18, 2025

Built scalable data pipelines using Python to extract, transform, and map structured diagnosis and procedure codes (ICD-10, CPT) from unstructured clinical text (EHRs), improving claim processing accuracy by 35% and reducing manual effort by 45%. Designed a cross-functional dashboard using Tableau and SQL, enabling real-time tracking of chart review volumes, facility-level QA status, and AI processing outcomes, improving visibility and decision-making across teams. Developed a hybrid rule-based plus LLM pipeline integrating vector similarity and deterministic logic to ensure code prediction accuracy. Collaborated with clinical, engineering, and executive teams to implement data validation, governance, and compliance across pipeline stages.

Data Analyst Intern at YWCA

August 31, 2023 - July 18, 2025

Designed and implemented ETL workflows in Python and PostgreSQL to clean, transform, and store large-scale financial records. Developed interactive Tableau dashboards to track budget allocation, expenditure patterns, and reimbursement timelines, enhancing transparency for the finance team. Streamlined check reimbursement pipeline, reducing processing cycle time by 6 days through automated data validation. Partnered with program managers and finance leads to define KPIs, improve data quality standards, and support real-time decision-making.

Analyst (Data Engineering) at Deloitte Consulting

May 31, 2022 - July 18, 2025

Built SQL-based pipelines and ETL workflows for Salesforce-based clinical systems and collaborated with clients to define data quality metrics. Developed a data extraction tool using AWS S3 OCR, Salesforce, SQL, and Java that reduced manual data entry by 80%. Secured a $1M project by delivering successful demonstrations to healthcare clients alongside the pre-sales team. Resolved over 400 support tickets, reducing recurring issues by 25% through root cause analysis and proactive fixes. Streamlined ticket workflows cutting average resolution time by 36 hours and coached/onboarded new hires. Collaborated with business leaders to translate challenges into data-driven solutions aligned with KPIs.