Naga S.
Lecturer (Data Science) @University Of Michigan - School Of Information
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WORK HISTORY
Lecturer (Data Science) @University Of Michigan - School Of Information
SIADS 505- Data ManipulationSIADS 515 - Efficient Data ProcessingSIADS 516 - Big Data: Scalable Data ProcessingSIADS 522 - Information Visualization ISIADS 622 - Information Visualization II• Enhanced student learning by developing engaging course materials and incorporating interactive lesson plans, improving student performance by 40%.• Mentored students in AI/ML applications, guiding them in developing multiple innovative AI/ML applications and solutions implemented in various projects and research initiatives.• Designed comprehensive assessments that improved knowledge retention and critical thinking skills.
EDUCATION
University of Michigan - School of Information
Masters, Applied Data Science
Indian Institute of Technology, Guwahati
MTech, Fluid and Thermal Engineering
University of Stuttgart
M.Tech Thesis, Two-Phase Flows in Pulsating Heat Pipes
Jawaharlal Nehru Technological University
BTech, Mechanical Engineering
SKILLS
ABOUT NAGA S.
Having more than 20 years of experience with multidimensional skill set - data engineering, machine learning, software development, team management, scrum master• Worked in a cross-functional team environment with people from multiple business units, vendors, countries, and cultures.• Familiar with gathering, cleaning, and organizing data for technical and non-technical personnel use.• Advanced understanding of statistical, algebraic, and other analytical techniques.• Extensive background in the full life cycle of the software development process, including requirements gathering, design, coding, testing, debugging, and maintenance.• Work well within a group and possess a high level of dependability.• Highly adaptable in quickly changing technical environments with powerful organizational skills.• Excellent problem-solving and leadership qualities with admirable communication and presentation skills.Specialties: • Programming: Python, PySpark, C++, Java, Shell scripting• Frameworks & Tools: TensorFlow, Databricks, Docker, Spark NLP, MLOps, Grafana• Databases: MySQL, PostgreSQL, Elasticsearch, AWS DocumentDB• Cloud & DevOps: AWS, Terraform, Git/GitHub, CI/CD Pipelines, Cloud-Hosted Analytics Platforms• Mac, Windows, Linux and Unix.
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