Data Analyst Machine Learning

Yashasri V

Data Analyst

Location: Mount Pleasant Mail: *.**********@*****.*** Ph: +1-313-***-**** LinkedIn PROFESSIONAL SUMMARY:

Dynamic and results-driven Data Analyst with 5+ years of experience in transforming complex data into actionable insights across banking, healthcare, and retail & e-commerce domains. Proficient in Python, R, SQL, and advanced machine learning techniques for predictive modeling, churn prediction, and fraud detection. Skilled in building secure ETL pipelines, developing interactive dashboards, and implementing regulatory compliance frameworks. Adept at leveraging cloud platforms such as AWS, Azure, and GCP for scalable data solutions. Known for optimizing data-driven strategies, enhancing decision-making, and enabling business growth through customer segmentation, CLTV modeling, and data storytelling across cross-functional teams. TECHNICAL SKILLS:

Programming Languages: Python, SQL, R, SAS, JavaScript, VBA Data Processing & ETL: Apache Spark (PySpark), Apache Airflow, Talend, SQL Server, Snowflake, Amazon Redshift, Google

BigQuery, Databricks

Data Visualization: Tableau, Power BI, Looker, Qlik Sense, Google Data Studio, Excel (Power Pivot, Power Query)

Machine Learning & AI: Scikit-learn, TensorFlow, Keras, XGBoost, LightGBM, CatBoost, Prophet, ARIMA, churn

prediction, recommendation engines, anomaly

detection, predictive modeling

Big Data & Cloud: Hadoop, Azure Synapse Analytics, AWS (S3, Redshift), Google Cloud Platform (GCP), Azure Data Lake

Domain Standards & Compliance: FHIR, HL7, EHR/EMR (Epic, Cerner), ICD-10, SNOMED CT, HIPAA, AML, KYC, Basel III, IFRS

9, GDPR, PCI DSS, CCPA, HITECH

Data Analysis & Statistics: SAS, Exploratory Data Analysis (EDA), cohort analysis, A/B Testing, sales forecasting, clinical outcome measurement, credit risk modeling, fraud

detection, pricing optimization

Automation & Scripting: Excel VBA, SQL Automation, Zapier, Google Apps Script

Version Control: Git, GitHub, GitLab

Other Skills: Jupyter Notebook, ggplot, data wrangling, regression analysis, data modeling, inventory analytics,

customer segmentation, CLTV modeling, data

storytelling.

PROFESSIONAL EXPERIENCE:

Fifth Third Bank – MI, USA

Data Analyst August 2024 – Present

Built and managed secure ETL pipelines using Apache Spark (PySpark), Apache Airflow, SQL Server, and AWS Redshift to process large-scale banking transaction data and risk assessment workflows.

Designed and deployed credit risk models and fraud detection systems with Python, R, SQL, and ML frameworks

(Scikit-learn, XGBoost, LightGBM), improving fraud detection rates by 28–35% and cutting operational losses by 22%.

Applied predictive analytics, churn prediction, and A/B testing to enhance customer engagement and optimize product pricing, driving an 18% increase in retention and revenue growth.

Ensured compliance with banking regulations (AML, KYC, Basel III, IFRS 9, GDPR, PCI DSS, CCPA) through automated reporting, monitoring, and compliance dashboards developed with SQL and Python.

Developed visually rich financial dashboards in Tableau to communicate KPIs, liquidity, and portfolio performance to executives and risk management teams.

Implemented real-time anomaly detection in transaction systems to prevent fraudulent activities and ensure secure digital banking operations.

Used Git and GitHub for version control to maintain integrity, transparency, and collaboration in data pipelines and analytical models.

Built customer segmentation and CLTV models to support targeted marketing campaigns and maximize customer lifetime profitability.

Accenture – India

Data Analyst July 2021 – August 2023

Engineered and maintained healthcare ETL pipelines using Apache Spark (PySpark), Apache Airflow, SQL Server, and Azure Synapse to deliver accurate and timely data flows across EHR and EMR systems.

Conducted in-depth exploratory data analysis (EDA) and applied clinical outcome measurement techniques to uncover treatment insights, resulting in measurable improvements in care quality.

Built time-series and predictive models (Prophet, ARIMA, anomaly detection, churn prediction) to forecast patient demand and optimize hospital resource allocation by 15%.

Implemented Azure Data Factory pipelines with secure connectors to EHR/EMR systems, ensuring HIPAA- compliant data ingestion and seamless integration with Azure Synapse for advanced clinical analytics and reporting.

Enforced strict compliance with healthcare standards and regulations (FHIR, HL7, ICD-10, SNOMED CT, HIPAA, HITECH, GDPR, CCPA) by integrating automated governance checks within data workflows.

Created dynamic Power BI dashboards to visualize patient outcomes, hospital operations, and population health indicators, empowering administrators and clinical leaders with real-time intelligence.

Applied advanced machine learning methods (Scikit-learn, TensorFlow, Keras) to develop predictive diagnostic tools, disease trajectory models, and personalized treatment recommendations.

Used A/B testing and cohort-based studies to assess the effectiveness of interventions, leading to evidence-based enhancements in patient engagement and care delivery.

Partnered with clinicians to transform raw datasets into actionable insights through data wrangling, regression modeling, and storytelling, supporting better decision-making at the point of care.

Automated recurring reporting workflows with SQL scripts and VBA, streamlining compliance documentation and reducing manual workload.

Deloitte - India

Data Analyst June 2019 – June 2021

Built and maintained scalable ETL workflows with Apache Spark (PySpark), SQL Server, Databricks, and Apache Airflow on Google Cloud Platform (GCP) to unify data from online stores, payment gateways, and sales channels.

Applied advanced forecasting methods (Prophet, ARIMA, XGBoost) to predict sales demand and optimize inventory planning, reducing stockouts by 15% and improving accuracy by over 20%.

Developed customer segmentation and lifetime value models using Python and Scikit-learn to power data- driven personalization and boost campaign effectiveness.

Designed interactive performance dashboards in Looker to monitor churn rates, promotional ROI, and real-time e-commerce sales metrics for business stakeholders.

Deployed A/B testing and dynamic pricing analytics to measure campaign impact and increase revenue from promotional activities.

Leveraged GCP BigQuery for real-time fraud detection and anomaly monitoring across high-volume transaction data, strengthening operational security.

Used Git/GitHub for version control, ensuring collaborative development and transparent tracking of analytics workflows.

Delivered actionable insights through data storytelling to guide merchandising, marketing, and supply chain optimization strategies.

EDUCATION:

Master’s in Information Systems (Major: Business Data Analytics) - Central Michigan University Bachelor’s in Computer Science & Engineering - Ellenki Engineering CERTIFICATIONS:

Certified to AWS

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