Machine Learning Data Science
Resume:
SUMA CHIDARA
***************@*****.***
https://www.linkedin.com/in/suma-chidara-873132178/ P R O F E S S I O N A L S U M M A R Y :
• IBM certified professional in Data Science and Machine Learning with extensive experience in Data Science and Business Analysis with hands-on experience in SQL, Python, Tableau, Power BI, and Excel.
• Orchestrated the development and deployment of machine learning models, significantly enhancing operational efficiency and the accuracy of geospatial data processing, contributing to more reliable digital map infrastructures.
• Integrated sophisticated machine learning algorithms to streamline operations, which resulted in a substantial improvement in system performance and user engagement.
• Employed advanced Natural Language Processing (NLP) techniques for the analysis and interpretation of user feedback, substantially enhancing the quality and efficiency of Points of Interest (POI) identification.
• Pioneered a collaborative approach in machine learning solution development, which translated into a quantifiable 15% improvement in overall operational workflow efficiency.
• Designed and led instructional sessions on machine learning applications, promoting an environment of continuous learning and skill advancement within technical teams.
• Directed the utilization of machine learning in quality assurance for mapping residential and commercial areas, achieving a notable increase in data accuracy and mapping precision.
• Leveraged Geographic Information Systems (GIS) and machine learning for advanced mapping attribution, significantly boosting data precision and contributing to more accurate environmental monitoring and planning.
• Innovated predictive models for agriculture, integrating AI with geospatial factors to enhance land suitability analysis, which supported farmers in optimizing crop selection and resource management... E X P E R T I S E :
• Machine Learning Model Development
• AI & ML Engineering
• Geospatial Data Analysis
• Data Processing & Analysis (Python, SQL, Spark)
• Cloud Technologies (AWS EC2, S3, Lambda)
• Natural Language Processing (Tokenization, NER, NLU)
• Version Control (Git)
• Big Data Technologies (Apache Spark)
• Statistical Analysis (Hypothesis Testing, Regression Analysis)
• Mathematics & Statistics (Linear Algebra, Probability, Statistics) P R O J E C T E X P E R I E N C E :
DALLAS DATA SCIENCE ACADEMY
MACHINE LEARNING ENGINEER, DALLAS, TX (DEC 2023 – CURRENT)
• Developed predictive models through the application of machine learning techniques, such as linear regression and boosting algorithms. Conducted thorough evaluations of model structures and compared the performance across various models.
• Engaged in feature scaling and engineering, as well as statistical modeling, utilizing Python.
• Undertook Exploratory Data Analysis (EDA) with the latest Python AI packages, delving into both internal and external datasets to pinpoint areas for efficiency enhancements.
• Utilized Tableau for the creation of informative dashboards. This effort in data visualization transformed complex data sets into easily understandable visual narratives, aiding stakeholders in making informed, data-driven decisions.
• Performed extensive data analysis with Python, exploring datasets in detail to uncover trends, patterns, and actionable insights, thereby impacting strategic business decisions.
• Executed meticulous data cleansing processes, which included the elimination of duplicate records and the management of data anomalies, to ensure the availability of high-quality, reliable data for further analysis and modeling tasks.
• Specialize in sentiment analysis using advanced text-to-text models such as Transformers, Llama and Generative AI, extracting actionable insights from customer feedback and social media data.
• Implement and fine-tune complex NLP algorithms, ensuring high accuracy in language interpretation for nuanced sentiment and context understanding.
• Enabled efficient speech-to-text conversion by integrating and fine-tuning OpenAI's Whisper model, enhancing the accessibility and analysis of voice data across platforms. APPLE (AI AND ML ENGINEER)
HYDERABAD, INDIA (JUN 2021 – AUG 2023)
• Drove the creation and execution of machine learning models to forecast and evaluate the impact of changes in complex digital infrastructures, leading to enhanced accuracy in geospatial data applications.
• Seamlessly integrated advanced machine learning algorithms, such as TensorFlow and PyTorch, into key operational workflows, yielding significant gains in digital mapping precision and performance.
• Implemented sophisticated Natural Language Processing (NLP) methodologies for in-depth analysis of user feedback, informing and enhancing Points of Interest (POI) accuracy and user satisfaction.
• Collaborated effectively with interdisciplinary teams to formulate and deliver innovative machine learning strategies, delivering a 15% uplift in operational efficiency and process optimization.
• Orchestrated comprehensive training programs on machine learning applications, cultivating a knowledge-rich environment, and bolstering the technical prowess of the team.
• Devised and standardized best practices for the deployment of machine learning models, ensuring robustness, scalability, and maintainability across various applications and platforms.
• Initiated and guided the adoption of AI-driven automation tools, resulting in a reduction of manual errors and increasing the speed of data processing tasks.
• Championed the integration of machine learning insights into business intelligence tools, providing stakeholders with advanced analytical capabilities for better decision-making. AMAZON (DATA ANALYST)
HYDERABAD, INDIA (JAN 2020 – JUN 2021)
• Championed the creation of machine learning models to enhance the mapping accuracy of residential and commercial areas, leading to significantly refined urban data systems.
• Undertook comprehensive statistical analyses of geospatial data sources, driving the adoption of data- centric strategies in mapping and planning operations.
• Implemented a suite of machine learning algorithms for quality control, significantly boosting the precision of mapping outputs.
• Merged Geographic Information Systems (GIS) with machine learning, resulting in a 20% enhancement in data attribution and mapping accuracy.
• Initiated and managed a continuous improvement protocol using machine learning feedback, refining data accuracy and mapping methodologies.
E D U C A T I O N & C E R T I F I C A T I O N S
• Masters, Remote Sensing and Geographical Information Systems. Major in ML Applications for GIS, Asian Institute of Technology, Thailand
• Bachelors, Computer Science and Engineering. Specialized in Data Analytics, India
• IBM, Python for Data Science and AI
• SQL, Tableau, and Python for Data Science and Artificial Intelligence, Dallas Data Science Academy
• AWS Data Analytics
• Google Generative AI, LLM and Responsible AI
• Coursera Master Course in AI and Machine Learning
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