Reema Kumari
Verified Expert in Engineering
Data Scientist and Developer
Samastipur, Bihar, India
Toptal member since June 9, 2021
Reema has 4+ years of experience in machine learning and data analytics across various projects, such as movie scheduling, cargo space optimization, loan recovery, and digital products. She has focused heavily on natural language processing in the digital product space, and she is proficient in Python and R. Reema is also an incoming student in the UCLA Master of Engineering program, focused on artificial intelligence.
Portfolio
Experience
- Data Analysis - 4 years
- Python 3 - 3 years
- Natural Language Processing (NLP) - 2 years
- Predictive Modeling - 2 years
- Generative Pre-trained Transformers (GPT) - 2 years
- Econometrics - 2 years
- Data Wrangling - 2 years
- Algorithms - 1 year
Work Experience
Senior Associate, Analytics
Zenon AI
- Optimized loan recovery across various channels for a leading US bank.
- Used gradient boosting to predict incremental loan recovery amounts from different channels.
- Consolidated various signal sources in SAS and performed innovative feature selection and modeling in H20.
Associate Data Scientist
Gartner
- Developed a plagiarism detector for a peer review platform, saving $2.5 million in gift card reimbursement and reducing manual moderation time by 50%.
- Enhanced the user search experience by suggesting typeahead expansions for search queries, leading to around $24 million in retention impact.
- Identified the most important questions asked and documents relevant to the question asked in a given user query.
- Used embeddings from language models (ELMo) to incorporate features for document recommendation.
Analytics Specialist
Opera Solutions India Pvt Ltd
- Developed movie clusters to predict optimal movie schedules for a large UK cinema chain and upsurged revenue by 23%.
- Built an ensemble model, using logistic regression and random forest to predict cargo show-up class with an error rate at or below 5%.
- Developed learning repositories for techniques such as non-negative matrix factorization.
- Conducted exploratory data analysis to optimize staffing across various projects.
Project History
Courts and Startups
This work is published as a chapter in the book entitled: Formal Contract Enforcement and Entrepreneurial Success of the Marginalized. The chapter is entitled: Opportunities and Challenges in Developments (pg 171-197).
Adoption of Balanced Use of Fertilizers
https://www.theigc.org/project/adoption-of-balanced-use-of-chemical-fertilizers-farmers-response-to-scientific-evidence-and-social-learning/Education
Bachelor's Degree and Master's Degree in Economics
Indian Institute of Technology (IIT), Kanpur - Kanpur, India
Skills
Libraries/APIs
Pandas, Natural Language Toolkit (NLTK), Matplotlib, Scikit-learn, TensorFlow, LSTM, NetworkX, Beautiful Soup, XGBoost, Stanford NLP
Tools
Seaborn, StatsModels, Gensim, Apple Keynote, STATA, Named-entity Recognition (NER), Stanford NER
Languages
Python 3, R, Python, C, SAS
Frameworks
Spark
Platforms
Anaconda, Amazon Web Services (AWS), H20
Other
Data Analysis, Economics, Econometrics, Algorithms, Natural Language Processing (NLP), Predictive Modeling, Logistic Regression, Linear Regression, Clustering, Client Presentations, Data Wrangling, Text Analytics, Word2Vec, GloVe, Tf-idf, Recommendation Systems, Gradient Boosting, Data Science, Machine Learning, Data Modeling, Generative Pre-trained Transformers (GPT), Excel 365, Calculus, Probability Theory, Statistics, Linear Algebra, Data Structures, Data Analytics, Deep Learning, BERT, Non-negative Matrix Factorization (NMF), Random Forests, K-means Clustering, Exploratory Data Analysis, Long Short-term Memory (LSTM), Presentations, Surveys, Data Visualization
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