Data Scientist Machine Learning

SUMMARY

URVI RAWAT

667-***-**** Baltimore, MD ****.*******@*****.*** GitHub Tableau

Results-driven Data Scientist with 3+ years of experience building AI solutions for healthcare. Proficient in predictive modeling, data visualization and natural language processing, leveraging cloud platforms for effective model deployment. Excellent communication skills for effective collaboration with cross-functional teams, complemented by a solid understanding of business fundamentals. SKILLS

Skills: Data Analytics, Data Visualization, Machine Learning, Deep Learning, Data Engineering, ETL Pipelines, Natural Language Processing, Cloud Platforms, Problem Solving, Cross-functional Team Collaboration, Agile Software Development, JIRA, LLMs, Java Data Analysis: SQL, NoSQL, Spark, R, Excel, Tableau, Power BI, Google Analytics, Google Optimize, Python, A/B Testing Model Building: Python (Scikit-learn, Tensorflow, Keras, PyTorch, PySpark, NLTK, Numpy, Pandas, Seaborn, Matplotlib) Model Deployment: Microsoft Azure, Amazon Web Services (AWS), Docker, Kubernetes, Postman, Swagger, REST APIs, Flask Certifications: Architecting with Google Cloud Platform (Google Cloud), Deep Learning (deeplearning.ai), Practical Machine Learning with Tensorflow (Google and IIT Madras)

EXPERIENCE

Business Intelligence Analyst (B2B) Molina Healthcare Baltimore, MD May 2024 – Present Fortune 500 Healthcare Organization and Insurance Provider

Analyzed insurance utilization and built an ML model for claims using Python and SQL, optimizing resource allocation by 15%

Collaborated with cross-functional teams to translate business needs into data-driven solutions, supporting client needs

Developed and optimized 10+ BI dashboards in Tableau, providing actionable insights increasing operational efficiency by 30% Data Scientist Intern (B2B) Nasdaq Boston, MA June 2023 – Aug 2023 Global Electronic Marketplace for Buying and Selling Securities

Developed a deep learning model using PyTorch and AWS Sagemaker to predict the volume of all large-cap symbols during the closing cross in Nordic markets, providing a 14.8% improvement over the NOII benchmark

Led stakeholder meetings to identify key requirements, design tailored solutions, review feedback and define success metrics Data Scientist (B2C) Bajaj Finserv Health India July 2021 – June 2022 Digital Healthcare Platform Offering Telehealth and Insurance Services

Implemented an audio prescription feature for virtual consultations employing Azure services and an NLP model (Tok2Vec), cutting time taken by doctors to fill an electronic medical record (EMR) by 48% and boosting appointments by 25%

Collaborated with doctors, software engineers and product managers to build a machine learning model (Python, MySQL, Microsoft Azure) for standardizing lab reports using NLP, resulting in a 95% reduction in manual workload

Created Flask APIs and deployed these models using Azure’s Kubernetes Service; enabled CI/CD in Azure DevOps

Increased product page conversion by 23% through A/B testing various CTAs, enhancing user engagement and decision clarity

Managed interactive dashboards in Tableau to monitor 15+ KPIs, analyzing product usage metrics with SQL and Google Analytics Data Scientist Symbiosis Centre for Applied Artificial Intelligence India Aug 2020 – June 2021 Interdisciplinary Research Centre driving Advancements in AI

Conducted a comprehensive literature review, analyzing over 25 language models and a wide range of relevant datasets

Built a conversational agent using DialoGPT (transformer model) leveraging Python, TensorFlow and AWS to provide virtual therapy, enhancing accessibility to mental health support Data Scientist Co-Op (B2C) Bajaj Finserv Health India Jan 2020 – Jul 2020 Digital Healthcare Platform Offering Telehealth and Insurance Services

Analysed the purchasing behaviour of 37mil leads in Spark, identifying 5+ areas of improvement in the lead management system

Built data pipelines in Azure Data Factory, integrating with Salesforce and reducing time taken to close a lead by 70%

Trained and deployed a lead classification model utilizing Python, MySQL, Flask and Azure Kubernetes Service, effectively prioritizing actions during sales campaigns and achieving a remarkable 56% increase in lead conversion rates EDUCATION

Master of Science in Engineering Management, Johns Hopkins University, Baltimore, MD 2022 – 2023 Bachelor of Science in Computer Science, Symbiosis International University, India 2017 – 2021 TECHNICAL PROJECTS

Breast Cancer Prediction [Python] – A binary classification problem leveraging ensemble learning and resampling to predict breast cancer using FNA test results

Cifar-10 dataset [Tensorflow] – Multiclass multicolored image classification of objects using transfer learning on ResNet50 Face Generator [Tensorflow] - A DCGAN (deep convolution generative adversarial network) used to create images of unique new faces

Neural Machine Translation [Tensorflow] - A seq2seq NLP model using attention mechanism made for translating French to English

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