Karan Talati Email & Phone Number

Tampa, FL, US

United States

As a Data Science professional with a Master’s in Data Science, I am seeking opportunities to apply my expertise in predictive analytics, machine learning, Generative AI, and data-driven decision-making. My previous role as a Data Analyst at Jay Cee Publications enabled me to enhance data accuracy, streamline data processes, and contribute to informed.

New Delhi, India

• At Jay Cee Publications, I spearheaded initiatives to enhance data management, reporting processes, and predictive analytics, significantly impacting stock management and financial performance.
• Developed an automated data cleaning pipeline using Python and SQL, improving data accuracy by 13%, enabling precise market and distribution analysis.
• Revolutionized sales reporting by implementing advanced SQL queries, reducing report generation time by 50%, allowing quicker stock adjustments and decision-making.
• Engineered Flask endpoints to automate data collection, reducing manual processes by 4 hours and increasing data completeness by 25%.
• Integrated data from five external sources, enhancing data accuracy by 15%, supporting better distribution insights.
• Created dynamic Tableau visualizations for key KPI tracking, enabling stakeholders to make informed decisions at a glance.

New Delhi, Delhi, India

• During my internship, I applied AI and machine learning to enhance marketing strategies and operational decisions.
• Developed interactive dashboards using tools like Tableau for real-time marketing performance insights, improving decision-making effectiveness by 12%.
• Built AI and deep learning frameworks with TensorFlow and AWS, boosting predictive analytics accuracy by 25%.
• Managed and analyzed datasets using Pandas and NumPy, ensuring high data accuracy for in-depth strategic analysis.
• Applied predictive modeling techniques to identify trends in marketing data, directly influencing strategy adjustments and improving overall marketing effectiveness.

• Contributed to a research initiative using image recognition and spatial analysis to monitor tiger populations and poacher activities. Built a Linear Regression model to forecast tiger populations with 92.18% accuracy.
• Applied computer vision techniques to detect and monitor movement patterns in real-time, utilizing image recognition models.
• Used spatial analysis to generate heat maps, highlighting areas of high poaching risk and tiger activity.
• Built a Linear Regression model to predict tiger populations, achieving a 92.18% accuracy using historical data on poaching, births, and deaths.
• Employed Python (Pandas, NumPy, Scikit-learn) for data preprocessing, feature engineering, and model development.
• Utilized heat map visualizations to aid conservation teams in identifying critical regions for tiger protection and anti-poaching measures.

Master'S Degree, Data Science, 3.8/4

B.E, Computer Science And Engineering