Sujith

Penugonda, Andhra Pradesh, India
Sujith
Experience: 2 years
Open to: Full-Time
Education: Bachelors
Availability: Immediate
Skills: GCP, Jira, Jupyter Notebooks, LLMs/ChatGPT, Matplotlib, MySQL, NumPy, pandas, Postman, Problem Solving, Python, scikit-learn, ServiceNow
Previously worked at: IT Service Companies, Startups
Assessment Score: 75
  • Proven Expertise in Data Science: With over two years of experience in machine learning, predictive modeling, and data analysis, successfully developed and deployed solutions that reduced fraud-related losses by 15% and enhanced predictive accuracy in key projects.
  • Strong Technical Foundation: Proficient in Python, SQL, Scikit-learn, and data visualization tools like Matplotlib and Seaborn. Skilled in leveraging advanced data science tools such as Google Colab, Jupyter Notebook, and Streamlit for optimized performance and impactful outcomes.
  • Professional Experience with Tangible Impact: At Ola Cabs, implemented machine learning models to detect fraudulent behavior, optimized feature selection, and engineered metrics like “NC” to improve decision-making processes. Reduced false positives by 25% and achieved an R-squared value of 0.94 in predictive analytics.
  • Notable Projects with Business Value: Delivered customer segmentation analysis using clustering techniques, driving a 15% increase in sales and customer retention. Built a job recommendation engine with optimized data processing strategies, enhancing system usability and reducing load times by 50%.
  • Educational and Certified Excellence: Holds a B.Tech in Computer Science and Engineering from Lovely Professional University and has completed certifications in data science, machine learning, and Python programming from leading platforms like Coursera and Udemy.
  • Collaborative Problem-Solving Skills: Adept at collaborating with cross-functional teams, diagnosing technical issues, and enhancing system efficiency. Demonstrated leadership in troubleshooting and improving database performance, achieving a 10% boost in data processing speed and increasing service uptime reliability.

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