Teja Arikati
Verified Expert in Engineering
Data Scientist and Developer
Teja is a versatile data scientist with over five years of experience and a postgraduate operations research (OR) degree from Cornell. His experience ranges from implementing end-to-end machine learning solutions to leading a team of data scientists and analysts. Teja is always ready to deliver production-quality results to any data science project.
Portfolio
Experience
Availability
Preferred Environment
Jupyter Notebook, Visual Studio Code (VS Code), PySpark, SQL, Scikit-learn, Apache Hive, Gurobi
The most amazing...
...thing I've achieved is developing and productionizing a company's first machine learning solution, which helped decrease manual labor costs by 25%.
Work Experience
Car Rental Fleet Owner
Self-Employed
- Built forecasting pricing models using ARIMA and LSTMs to forecast demand and optimal pricing of rental cars, increasing monthly revenue by 15%.
- Determined the best cars to include in the fleet by calculating the vehicles' time value and expected rental income by car.
- Built a passive income stream by hiring employees to manage a self-funded fleet of seven Jeeps on Maui.
Senior Data Scientist
Citi
- Led the research and Python production deployment of a boosted-tree classifier to calculate the risk score of an email or chat, reducing false positives by 50% and yearly manual review costs by $500 thousand.
- Developed and deployed NLP topic detection models, which improved recall by three times while reducing time to deployment by 70% through implementing few-shot learning, active learning, and robust labeling techniques.
- Developed an 80% accurate NLP sentence similarity engine by utilizing a domain-specific Word2vec model trained on 300GB of e-communications with PySpark ML libraries.
- Reduced compute and storage requirements by 50% in the Hive big data environment by building and optimizing terabyte-sized data stores using PySpark.
- Developed and deployed real-time model monitoring tools, which reduced model deviance detection time from two days to 15 minutes.
- Mentored and led a team of data analysts and data scientists through the development of standardized data science practices and documentation frameworks.
- Automated the business rules extraction from unstructured text utilizing data-driven rule extraction methods such as RuleFit and decision trees.
- Researched and fine-tuned BERT to identify specific low-occurrence topics in text and showed improved recall by 30%.
Experience
Image Search Optimization
Manufacturing Flow Shop Optimization Program
Hummus Company Delivery Optimization and Demand Forecasting
I built a Python program to calculate optimal daily delivery routes to customers. Using historical delivery data, I modeled customer reliability using logistic regression with 95% accuracy. Utilizing customer reliability scores for different time windows and the OpenStreetMap API for navigation, I modeled a delivery optimization problem using Python and Gurobi. Using the optimal daily delivery schedule output from this program, Baba Hummus completed 20% more deliveries and reduced spoilage costs by 10%.
In addition to this optimization project, I developed a demand forecasting model to predict future demand for 10 different hummus products. I built ARIMA and SARIMA models in Python to predict daily and weekly demand of hummus. In testing, MAPE improved from 10% to 2%.
Education
Master's Degree in Informatics and Applied Mathematics
Cornell Tech - New York, NY, United States
Bachelor's Degree in Industrial Engineering
California Polytechnic University - San Luis Obispo, California, United States
Skills
Libraries/APIs
PySpark, Scikit-learn, XGBoost, Matplotlib, Rulefit, LSTM, TensorFlow
Tools
StatsModels, Seaborn, Gurobi
Frameworks
Business Rules Engine
Languages
SQL, Python
Paradigms
Data Science, Linear Programming
Platforms
Jupyter Notebook, Visual Studio Code (VS Code)
Storage
Apache Hive
Other
Machine Learning, Supply Chain Optimization, Natural Language Processing (NLP), ARIMA, Forecasting, ARIMA Models, Decision Trees, Linear Optimization, Logistic Regression, Time Series Analysis, Data-driven Decision-making, Data Visualization, Data Aggregation, Data Analysis, Data Analytics, Exploratory Data Analysis, GPT, Generative Pre-trained Transformers (GPT), Operations Research, Optimization, Process Improvement, Active Learning, Artificial Intelligence (AI), Supply Chain Management (SCM), SARIMA, Pricing Models, Demand Planning, BERT, Mixed-integer Linear Programming, Logistics, Decision Modeling, Deep Learning, Car Rental
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