Srinivas Chagantipati

Data Scientist with expertise in statistical analysis, predictive modeling, and data-driven decision-making. Adept at designing and implementing machine learning models to extract meaningful insights and optimize business processes. Strong background in data wrangling, feature engineering, and model deployment. Passionate about leveraging data science techniques to solve complex problems and enhance operational efficiency. Experienced in collaborating with cross-functional teams to develop scalable solutions that drive innovation and business growth.

• Strong foundation in data science, machine learning, and statistical analysis.
• Experience in automating data workflows and reporting to enhance decision-making.
• Proficiency in cloud computing (AWS, Google Cloud) for scalable data solutions.
• Excellent communication skills with the ability to translate complex data insights into business strategies.
• Continuous learning mindset, actively expanding knowledge in AI, cloud technologies, and data engineering.

• HR Analytics Dashboard: Designed an interactive dashboard in Power BI to analyze employee performance and attrition trends, integrating real-time HR data to track key performance indicators (KPIs) such as retention rates, employee engagement, and productivity. The dashboard enabled HR teams to identify workforce trends, forecast attrition risks, and implement strategic workforce planning. Provided actionable insights that helped HR teams enhance employee satisfaction and optimize talent retention strategies.
• Developed a predictive system for assessing liver disease risk based on individual blood test reports. Leveraging various machine learning algorithms, we identified the most accurate model. Our user-friendly system prompts individuals to input their test .details, allowing timely risk assessment and early intervention. Because, as they say, ‘An ounce of prevention is worth a pound of cure.
• Developed an innovative system for COVID-19 awareness and hospital bed demand prediction. Leveraging data visualization, the project provides real-time insights through graphical representations. Additionally, explored arrest rates and probable cause considerations, enhancing law enforcement decision-making.