Data Analyst Machine Learning

Venkata Sai Sanjay Pendela Data Analyst

Location: Texas, USA Mail: ********.*******@*****.*** Ph: 281-***-**** LinkedIn:www.linkedin.com/in/sanjay-pendela

PROFESSIONAL SUMMARY

Data Analyst with around 3 years of experience in driving data-driven decision-making across diverse industries, including healthcare and finance.

Expertise in data analysis, visualization, and predictive modeling utilizing a range of tools and technologies such as Python (Pandas, NumPy, Scikit-

learn), SQL, Tableau, Power BI, Hadoop, Hive, AWS, Google BigQuery, Jira, Agile methodologies. Proven ability to leverage machine learning

algorithms, statistical analysis, and data mining techniques to extract valuable insights from complex datasets, improve operational efficiency, and

mitigate risks. Strong understanding of data governance, regulatory compliance, and data security best practices.

TECHNICAL SKILLS

Data Analysis & Modeling: Scikit-Learn, TensorFlow, Keras, Logistic Project Management & Collaboration: Jira, Agile, Scrum, Project

Regression, Decision Trees, K-means, K-medoids, Anomaly Detection Documentation, Task Management, Knowledge Sharing

Data Wrangling & Cleaning: Python (Pandas, NumPy), Data Cleansing, Statistical Analysis: SPSS, Statistical Reporting, Data & Regression

Data Transformation, Data Quality Assessment Analysis

Data Visualization: Tableau, Power BI, SPSS, Interactive Dashboards, Compliance & Security: HIPAA Compliance, Data Encryption, Data

Key Performance Indicators (KPIs) Privacy Regulations

Machine Learning: Supervised Learning, Clustering Algorithms, Data Mining & Analytics: Customer Segmentation, Credit Risk Scoring,

Predictive Modeling, Model Deployment Portfolio Risk Analysis, A/B Testing

Databases & Data Warehousing: SQL Server, Oracle, Google BigQuery, Data Reporting: Reporting Automation, Business Insights, Actionable

Hadoop, Hive, Data Warehousing, SQL Query Optimization Reports

ETL & Data Integration: Apache NiFi, SSIS, ETL Processes, Data Flow Version Control & Collaboration: Git, GitHub, Version Control,

Automation, Data Extraction, Data Transformation Collaborative Development

Data Standards: FHIR, HL7, Data Interoperability, Healthcare Data Data Standards Compliance: RBI Guidelines, Regulatory Compliance,

Standards Data Privacy

Cloud Computing: AWS, Google Cloud Platform (GCP), Cloud Data

Storage, Scalable Data Solutions

EDUCATION

Master of Business Analytics - University of Houston, Texas, USA. Bachelor of Business Administration - KL University, Vijayawada, India.

PROFESSIONAL EXPERIENCE

Data Analyst Cigna Healthcare – TX Jan 2024 - Present

o Spearheaded the integration of diverse healthcare data systems, including EPIC, Cerner and Meditech, utilizing Talend to streamline workflows and

achieve a 30% reduction in data retrieval time, thereby enhancing decision-making processes.

o Designed and implemented interactive dashboards in Tableau, enabling real-time visualization of patient flow and resource allocation, which

resulted in a 20% increase in operational efficiency across clinical departments.

o Rigorously ensured adherence to HIPAA regulations throughout all data handling processes by implementing advanced data encryption protocols

and safeguarding sensitive patient information against unauthorized access.

o Executed comprehensive data wrangling & cleaning processes using Python libraries such as Pandas and NumPy, effectively preparing complex

healthcare datasets for in-depth analysis and reporting

o Crafted and optimized intricate SQL queries for data extraction and analysis from SQL Server and Oracle databases, enabling precise insights into

patient care metrics and operational performance.

o Developed and implemented efficient ETL processes using Apache NiFi, automating data flow between disparate healthcare systems and enhancing

data accessibility for analytical purposes.

o Applied FHIR and HL7 standards to ensure seamless data integration and interoperability across various healthcare platforms, promoting cohesive

data exchange and collaboration.

o Built and deployed sophisticated machine learning models using TensorFlow and Keras for accurate diagnosis predictions, contributing to improved

clinical outcomes and patient safety.

o Designed and maintained a scalable cloud-based data warehouse in Google BigQuery, optimizing data storage and retrieval processes to support

large-scale healthcare analytics.

Data Analyst Smart AI – India Jan 2021 - Nov 2022

o Implemented a credit risk scoring model using machine learning algorithms (Logistic Regression, Decision Trees) that improved loan approval

accuracy and reduced non-performing loans by 8%.

o Designed and built a customer segmentation model using clustering algorithms (K-means, K-medoids) to identify high-value customer segments

and tailor marketing campaigns, leading to a 20% increase in customer engagement and a 10% uplift in cross-sell/up-sell revenue.

o Developed and maintained a data warehouse using Hadoop and Hive to store and process large volumes of transaction data from various sources,

enabling real-time data analysis and faster insights for business decisions.

o Created interactive dashboards using Power BI to visualize key performance indicators (KPIs) such as customer churn rate, loan delinquency and

portfolio risk, providing actionable insights to senior management for proactive risk mitigation.

o Automated data ETL processes using SSIS to improve data quality & efficiency, reducing manual effort & minimizing data inconsistencies. Utilized

Agile methodologies for project management, ensuring flexibility & adaptability to changing business needs.

o Conducted data quality assessments & implemented data cleansing techniques to ensure data accuracy & integrity, improving the reliability of

analytical models & report. Leveraged cloud computing technologies such as AWS to scale data processing capabilities & reduce infrastructure cost

o Ensured compliance with all relevant regulatory requirements, including RBI guidelines and data privacy regulations, throughout the project

lifecycle. Maintained documentation for all data models, analytical processes, and reports to facilitate knowledge sharing and future maintenance.

o Implemented fraud detection models using anomaly detection algorithms and machine learning techniques, reducing fraudulent activities and

safeguarding the bank's assets.

Contact this candidate