Priyanka Shah Email and Phone Number
I am a results-driven Data Scientist with extensive experience in transforming complex data into actionable insights that drive data-informed decision-making. My expertise lies in leveraging Machine Learning algorithms, Deep Learning techniques, and Statistical Modeling to tackle challenging business problems. Proficient in programming with Python, R, and SQL, I utilize advanced data visualization tools like Tableau and Power BI to present insights clearly and effectively.Throughout my career, I have developed a strong command of Natural Language Processing (NLP), Time Series Analysis, and Predictive Analytics, complemented by experience in Big Data technologies such as Apache Spark and Hadoop. I am highly skilled in data wrangling and automating data pipelines through ETL processes, and I have worked extensively with Cloud Platforms (AWS, Azure, GCP) to create scalable data solutions.My analytical capabilities are further enhanced by my proficiency in A/B Testing, Hypothesis Testing, and advanced Mathematical Optimization techniques, allowing me to contribute to business growth and operational efficiency.Key Achievements- Customer Segmentation Models: Developed customer segmentation models at Dollar General that improved targeted marketing strategies, boosting customer engagement.- Inventory Forecasting: Built Time Series forecasting models that optimized stock levels and minimized overstock, significantly improving inventory management.- Credit Risk Models: Created and deployed credit risk models at Wells Fargo, enhancing credit evaluation processes and reducing risk exposure.- Fraud Detection: Designed fraud detection algorithms that utilized Anomaly Detection techniques, resulting in a measurable decrease in fraudulent transactions.- Predictive Analytics in Healthcare: Developed predictive models at Cigna Healthcare that forecasted patient claims, reducing processing times and optimizing resource allocation.- Automated Data Pipelines: Streamlined data accessibility by automating ETL processes using Apache Airflow and NiFi, enhancing operational efficiency across teams.- Dynamic Dashboards: Created interactive dashboards in Tableau and Power BI that enabled real-time decision-making for store managers and cross-functional teams.- I am passionate about using data to solve real-world problems and continuously seek opportunities to expand my skills and contribute to impactful projects. Let’s connect and explore how we can leverage data to drive success!
Dollar General
View- Website:
- dollargeneral.com
- Employees:
- 39319
-
Data ScientistDollar General Dec 2022 - PresentNew York, United StatesWorked on developing a customer segmentation model using Python and Scikit-Learn to classify shoppers based on their purchasing behaviors and demographics. By leveraging Market Basket Analysis with the Apriori Algorithm, I uncovered associations among products, which enabled tailored promotions for each customer segment. This initiative significantly enhanced Dollar General's ability to implement personalized marketing strategies, leading to improved customer engagement and increased sales. I presented my findings through dynamic dashboards created in Tableau and Power BI, providing the marketing and merchandising teams with actionable insights to drive customer-centric strategies and optimize their campaigns.Key Contributions: - Developed segmentation models that optimized targeted marketing strategies.- Built forecasting models, leading to improved stock levels and reduced overstock.- Analyzed datasets to recommend strategies that increased sales across various stores.- Conducted Market Basket Analysis to inform effective product placement and promotion strategies.- Automated data pipelines, enhancing efficiency for the analytics team. -
Data ScientistJpmorgan Chase & Co. Aug 2020 - Nov 2022New York, United StatesI conducted Natural Language Processing (NLP) on customer feedback to analyze sentiment and pinpoint areas for service improvement. Utilizing Time Series Analysis, I monitored trends in customer satisfaction over time, uncovering valuable insights into service performance. By integrating data from various sources through ETL pipelines and processing feedback in Apache Spark for scalability, I ensured a robust analysis. I presented my findings using interactive dashboards in Power BI and Tableau, empowering customer service teams to proactively address pain points. Additionally, I implemented A/B Testing on service adjustments to measure their impact on customer satisfaction and retention.Key Contributions:- Developed credit risk models using advanced algorithms, improving assessment processes.- Analyzed customer feedback with NLP, driving service improvements and satisfaction enhancements.- Designed algorithms that reduced risk exposure by identifying potential fraudulent transactions.- Conducted Time Series Analysis to inform resource allocation and predict financial trends.- Built ETL pipelines in Apache Spark for efficient processing of financial data.- Employed Power BI and Tableau to create visualizations that enhanced transparency and informed decision-making. -
Data ScientistCigna Healthcare Jan 2019 - Jul 2020New York, United StatesI implemented Sentiment Analysis using Natural Language Processing (NLP) to evaluate patient feedback, uncovering trends in satisfaction and identifying areas for improvement in healthcare services. Leveraging R for text data preprocessing and analysis, I extracted insights that informed strategies to enhance patient experiences. I designed automated workflows with Apache NiFi and ETL processes to streamline data ingestion and integration. My findings were presented through Looker dashboards, equipping healthcare teams with real-time insights to boost patient engagement and service quality.Key Contributions:- Reduced claims processing time through predictive modeling, improving resource allocation.- Enhanced customer experience by analyzing patient feedback with sentiment analysis.- Supported preventive healthcare measures by predicting chronic disease risks.- Improved data accessibility via automated claims processing pipelines.- Increased transparency in decision-making through dashboards visualizing patient metrics.- Validated clinical improvements through collaborative A/B testing with stakeholders.
Priyanka Shah Education Details
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Computer Science
Frequently Asked Questions about Priyanka Shah
What company does Priyanka Shah work for?
Priyanka Shah works for Dollar General
What is Priyanka Shah's role at the current company?
Priyanka Shah's current role is Data Scientist | Expert in Customer Segmentation, Sentiment Analysis, and Data Visualization | Driving Insights for Enhanced Customer Engagement and Service Quality.
What schools did Priyanka Shah attend?
Priyanka Shah attended The City University Of New York.
Who are Priyanka Shah's colleagues?
Priyanka Shah's colleagues are Anaya Hairston, Kimberly Edwards, Jennifer Walters, Derius Davis, Crystal Walden, Chad Smith, Kelsey Waldrop.
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Priyanka Shah
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Priyanka Shah
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