prachi – Data Scientist & Machine Learning Engineer

About Me

A Data Scientist and a Machine Learning Engineer with around 4 years of industry experience using ML to solve high-impact business problems. Expertise includes machine learning, deep learning, statistical analysis, data …

A Data Scientist and a Machine Learning Engineer with around 4 years of industry experience using ML to solve high-impact business problems. Expertise includes machine learning, deep learning, statistical analysis, data modeling, data engineering, computational optimization, and natural language processing
Experienced in the US Healthcare and Supply Chain sectors with a specialization in NLP, Machine Learning, and Deep Learning. Proficient in Python and SQL, and adept at managing both structured and unstructured data sets, excelling in data acquisition, validation, predictive modeling, and visualization.
Proficient with Google Cloud Platform tools, including Cloud Run, Cloud Functions, Pub/Sub, AutoML, and BigQuery for the efficient deployment and management of AI applications.
In-depth knowledge of RDBMS, particularly MySQL, with expertise in database operations like normalization, clustering, and query optimization.
Skilled in extracting data to create value-added datasets for targeted customer analysis using Python, R, Azure, and SQL. Built a near-real-time API that successfully detects and reduces errors in clinical notes by 65%, significantly enhancing document quality.
Proficient with PyTorch, Fast AI, CUDA, Hugging Face, NLTK, TensorFlow, Keras, and related deep learning platforms like RNN, LSTM, and LLM (ROBERTa).
Designed compelling visualizations using Tableau, effectively publishing and presenting data narratives on web and desktop platforms. Extensive experience implementing various machine learning algorithms, including but not limited to LDA, Naive Bayes, Decision Trees, and SVM.
Adept at performing exploratory data analysis using dplyr in R and pandas in Python. Proficient with data modeling tools such as Erwin, Power Designer, and RStudio. A solid grounding in statistics, mathematics, and analytics, underpinning a robust understanding of business operations and decision-making.
Advanced understanding of containerization with Docker, version control with Bitbucket and GitHub, and continuous integration/continuous deployment (CI/CD) with Jenkins.
Expert in crafting insightful visualizations using Tableau, ggplot2, Power BI, Streamlit, and Google Looker Studio. Well-versed in foundational machine learning models, including regression, random forests, boosting, and neural networks, among others.
Engineered an NLP engine capable of generating clinical notes from transcripts, harnessing the Roberta LLM model for precise contextual error detection. Proficient in statistical and programming languages, including R, Python, C, C++, Java, and SQL, with experience in the Anaplan forecasting tool.
Optimized MySQL database operations, achieving a 70% increase in query efficiency and a 30% decrease in server load through advanced clustering and normalization techniques.
Exhibited effective communication skills and a keen understanding of project timelines and dependencies. collaborative collaborator and initiative-taking individual with a solid grasp of Agile methodologies and Lean techniques, actively engaging in Agile ceremonies and Scrum meetings.

Experience

datascientist

Questrade

Sep 2022 - Present · 3 years 9 months

Data Scientist Job Description: Role, Responsibilities & Skills
By Simplilearn
Last updated on Jul 10, 2023106993
Data Scientist Job Description: Role, Responsibilities, Skills Required & More
Table of Contents
Data Scientist Job DescriptionData Scientist Roles and Responsibilities: What Does a Data Scientist Do?Data Scientist SkillsHow to Become a Data ScientistHow Much Do Data Scientists Make?View More
The data scientist is a relatively new key player in organizations — a new breed of analytical data experts. They are part mathematicians, part computer scientists, and they rule the world of big data. Businesses today are wrestling with volumes of unstructured information that’s a virtual gold mine, which can help boost revenue when unearthed. But they really need professionals who can dig in and find valuable business insights, sifting through the useless chaff and finding the precious nuggets of data. That is what the data scientist does; that is why they are highly sought after

Skills

Python Machine Learning NLP SQL TensorFlow Deep Learning AI Azure MLOps Data Science Statistical Analysis Data Modeling Data Engineering Computational Optimization Natural Language Processing Google Cloud Platform Cloud Run Cloud Functions Pub/Sub AutoML BigQuery MySQL Normalization Clustering Query Optimization PyTorch FastAI CUDA Hugging Face NLTK Keras RNN LSTM LLM Roberta Tableau LDA Naive Bayes Decision Trees SVM dplyr pandas Erwin Power Designer RStudio Statistics Mathematics Analytics Docker Bitbucket