Daniel O.
Data Scientist

Skills

Sql

Python

Amazon Aws

Google Cloud

Daniel is available for hire

Hire Daniel O.

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Bio

A professional with four years of experience specializing in Python, SQL, Statistics, and Big Data, with a strong background in Machine Learning and Deep Learning techniques spanning from exploratory analysis to deployment via RestAPI. Demonstrates robust problem-solving skills and excels in graphical and data storytelling using libraries such as SKLearn, Numpy, Matplotlib, Pytorch, Pandas, and Tensorflow. Possesses proficiency in computer vision, particularly for tasks such as tracking, classification, and autoencoders utilizing OpenCV. Currently focused on the development of NLP models using LLMs for chatbots.

Data Scientist
3/1/2023 - Present

Proficiency developed in creating and deploying models for inventory availability using sklearn, Tensorflow, and PyTorch. Crafted RestAPIs for model deployment and trained models extensively. Leveraged expertise in developing language models using LLM for chatbot creation. Managed data flow and ETL processes, and conducted statistical analysis for model comparison using techniques such as cross-validation, and P-Value analysis. Produced analytical comparison graphs and performed in-depth data discovery. Utilized tools and frameworks including SQL, NoSQL, Seaborn, and Matplotlib. Demonstrated technical skills in Python, artificial intelligence, machine learning, deep learning, data analysis, statistics, and REST APIs. Gained substantial experience working with Amazon Web Services and handling big data within data science projects.
Data Scientist
2/1/2020 - 2/1/2023

Developed and deployed machine learning and deep learning models to predict and monitor user behavior, purchase preferences, and target audience. Engineered ad placements designed to enhance visibility and profitability in inventory. Executed tasks involving classification, regression, clustering, and time series models, alongside robust reporting visualizations.

Acquired and demonstrated skills in Python, machine learning, deep learning, data analysis, business intelligence (BI), and statistical methods. Leveraged capabilities in web scraping, SQL, and NoSQL databases, while utilizing Amazon Web Services for cloud-based operations. Proficient in creating detailed reports and dashboards using Microsoft Power BI, underlining a solid foundation in data science.