Data Scientist

Prabhu Teja Gande

Potsdam, NY, USA +1-315-***-**** Email LinkedIn Github

EDUCATION

Clarkon University, Potsdam, New York, USA. August 2023 - December 2024 Master of Science in Applied Data Science GPA:3.7 Jawaharlal Nehru Technological University-Anantapur, India. July 2017 - July 2021 Bachelor of Technology in Computer Science and Engineering GPA:7.8 TECHNICAL PROFICIENCY

Languages: Python, SQL, R, Java, C/C++, Scala, Julia. Data Analysis Tools: Jupyter Notebook, Pandas, NumPy, Matplotlib, Seaborn, SciPy, Plotly. Database Systems: MySQL, PostgreSQL, MongoDB, Oracle, SQL Server, Cassandra. AWS Services: EC2, S3, Lambda, RDS, Redshift, SQS, Glue, Athena, SageMaker. Machine Learning & AI: Scikit-Learn, TensorFlow, Keras, PyTorch, NLP, Deep Learning, XGBoost. Other Skills: Data Visualization, ETL, Data Wrangling, Preprocessing, Statistics, Git, REST APIs, Docker, Kubernetes, Linux. WORK EXPERIENCE

Graduate Assistant Clarkson University August 2023 - Present

• Spearheaded the planning and execution of multiple AI-driven research projects, resulting in a 15% increase in research output and a 10% improvement in project completion times.

• Streamlined data collection and storage processes using automated ETL pipelines, reducing data processing time by 20% and enhancing data accuracy by 15%. Utilized advanced organizational skills and data management techniques.

• Developed comprehensive course materials incorporating machine learning models and real-world examples, boosting student en- gagement by 25% and improving test scores by 10%. Focused on curriculum development and effective data presentation. Reference Data Analyst Deutsche Bank India, Bangalore, India February 2023 - July 2023

• Led investigations into potential breaches within the CTOC project using advanced anomaly detection algorithms, reducing associated risks by 40% and improving data accuracy by 30% through detailed monitoring and analysis of trading data.

• Conducted in-depth Exploratory Data Analysis (EDA) by extracting, cleaning, and processing large datasets using SQL and MS Excel, increasing analysis efficiency by 25% and providing actionable insights that informed trading strategies.

• Developed automated reporting tools using Python, increasing report generation speed and accuracy by 20%. Integrated data from 10+ sources, reducing manual reporting time by 30 hours monthly, and providing real-time insights for 50+ stakeholders. Data Analyst AXTRIA Pvt Ltd., Hyderabad, India January 2022 - February 2023

• Designed and implemented interactive dashboards using Tableau and Power BI, enhancing user experience by 35% and operational efficiency by 40% through advanced data visualization and cross-functional collaboration.

• Engaged with clients to translate complex business requirements into actionable machine learning models, delivering comprehensive reports that improved decision-making by 30%.

• Conducted extensive training sessions for internal teams on data visualization best practices, resulting in a 25% increase in team competency and proficiency with Tableau and Power BI tools. PROJECTS

ADSB-project Python, Signal Processig, Pandas, Data Visualization

• Engineered and implemented an ADS-B signal processing system using Python, successfully decoding over 500,000 ADS-B messages with a 95% accuracy rate, enhancing aircraft tracking capabilities.

• Optimized data handling and processing pipelines to manage and analyze 2TB of raw ADS-B data, reducing data processing time by 40% through the use of efficient algorithms and multiprocessing techniques. Future Stock Predictions Python, Keras, Numpy, Pandas

• Developed and implemented machine learning models to predict stock prices with an accuracy of 85% using Python and Scikit-Learn, improving forecast precision by 20% compared to traditional methods.

• Processed and analyzed over 1 million rows of historical stock data using Pandas and Numpy, reducing data preprocessing time by 30% through efficient feature engineering and data cleaning techniques. Smart Plant Leaf Disease Detection and Classification Deep Learning, TensorFlow, Keras, Tuning

• Developed a plant disease recognition model using deep convolutional neural networks (CNNs), achieving a 95% accuracy in classifying 13 different types of plant diseases from healthy leaves. Implemented advanced preprocessing techniques in leaf segmentation.

• Trained and validated the model on a dataset of 10,000 leaf images, optimizing hyperparameters to reduce training time by 20%. Utilized TensorFlow and Keras, resulting in a 10% improvement in disease detection accuracy over traditional methods. ACHIEVEMENTS

• Recognized for exceptional performance and results within 9 months of starting my first job, earning a Performance Excellence Award (Fresh Hire category).

• Mentored and guided numerous individuals, facilitating their successful placement in diverse roles such as Developers, Testers, and Data Analysts in prominent multinational corporations (MNCs). TECHNICAL COURSE

DataCamp Advanced Python Online JAN 2021 – APRIL 2021

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