Requests
60
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Network Power<100 people
Roles
🔥66%
Startup Founder
✔️66%
IT
✨66%
Business Owner
Geos
🇦🇪33%
United Arab Emirates
🇮🇳33%
India
Work Background
The Chefs' WarehouseData Scientist
Jan. 2024 - May. 2024Ridgefield, Connecticut, United States · Remote
DataracyData Scientist (Freelance)
May. 2022 - Jan. 2024San Francisco Bay Area● Generated an analytics dashboard by leveraging Facebook Prophet and two years of eCommerce datasets to create a sample forecasting model, accurately predicting store monthly sales for the next six months for sales forecasting
● Built fuzzy matching tool using (AI) Natural Language Processing (NLP) tools including TF-IDF for data cleaning which increased productivity by saving two hours of manual data labeling each month
QVCAssociate Data Scientist
Sep. 2020 - May. 2022Pennsylvania, United States● Owned a graph-based, collaborative filtering product recommendation model that drove two strategic initiatives in the personalization of the company’s B2C e-commerce site, decreasing expenses
● Partnered with eCommerce team to improve conversion rates by ~5% by developing a (ML) gradient-boosted tree model that identified critical site features for driving sales and validated earlier findings from the testing team
● Designed features from multiple data sources using Python and SQL for improving an existing airtime attribution model which improved the model by ~5-10% to better understand customer purchasing behavior.
CuyanaData Science Intern
Oct. 2019 - Jun. 2020San Francisco Bay Area● Developed a data-driven marketing attribution model using 4th-order Markov chains, enabling the organization to gain valuable insights and optimize marketing spend by saving ~3% in marketing expenses
● Created a customer propensity scoring model utilizing (ML) gradient boosting (xgboost) to identify critical site features, which was then leveraged by the digital team to enhance the website and improve conversion rates
● Combined SQL and Tableau for ad hoc data analysis of payment methods visualized in a dashboard that delivered data-driven insights which were leveraged by the digital marketing team on a daily basis
● Utilized Pytorch to train a neural network to produce product embeddings, which were leveraged for a recommendation system on website product pages - increasing page views for the recommended products by ~2-6%
● Leveraged an artificial neural network in statistical modeling of repeat purchase behavior which accurately predicted second purchases with a 97% accuracy rate, enabling the organization to improve customer retention by ~4%
Webster BankFinance Intern- Enterprise Analytics
Mar. 2019 - Jun. 2019Waterbury, Connecticut• Pulled data from the Twitter API to create social media sentiment reports and benchmarking tools used by the bank daily
• Developed predictive model for customer attrition using logistic regression in Python packages scikit learn and statsmodels which served as a proof of concept for the bank’s integration of Python into its technology stack
NYU ShanghaiData Science Intern
Sep. 2018 - Dec. 2018Shanghai City, China• Analyzed bus networks in Brooklyn, New York to recommend changes to optimize bus routes
• Visualized and explored GTFS and network data in Python to support academic research
SideChefAssociate Community Manager
Aug. 2014 - May. 2015Shanghai City, China• Entered data into company database and aided data quality assurance
• Coordinated outreach to food bloggers and YouTubers to arrange partnerships
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