Abhishek Singh

Developed and deployed machine learning models using Python, TensorFlow, and Scikit-learn to predict churn, forecasting, risks and segmentations. Develop and maintain predictive models and algorithms using statistical and machine learning techniques, such as regression and classification analysis, decision trees, neural networks, and ensemble methods. Work on problems from various domains like NLP, Recommendation engine, computer vision , Proficient in Training Detection/Classification/Segmentation Models. Built and deployed machine learning models on AWS and deployed them using Docker and Kubernetes. Exposure in Hadoop and Spark for processing large-scale datasets and integrating them with machine learning models. Conducted A/B testing and designed experiments to validate model performance and improve accuracy. Developed dashboards and visualizations using Tableau and Power BI to present data insights to stakeholders and executive leadership. participate in complete project cycle i.e. understanding a problem statement, data gathering, analyzing data, Cleaning data, implementing appropriate ML/AI solution and deploying it to Production.

Analyzing data using statistical techniques and providing reports. Building advanced statistical models, algorithms and trend analysis in order to discover predictive insights related to network and business objectives. Acquiring data from primary and secondary sources and maintain data systems. Identifying, analyzing, and interpreting trends or patterns in complex data sets. Translate operator business objectives into business intelligence trough regressive data analytics.