Rituraj Kumar

Acted as a senior data and MLOps engineer at Zeals, where I spearheaded the development of a chatbot recommendation and analytics platform and handled the implementation of a scalable data warehouse for the analytics platform.

The platform was designed to prioritize personalized user interactions and campaign optimization, aiming to improve user engagement and enhance campaign performance through advanced data analysis and machine learning techniques.

Developed a healthcare analytics platform on Google Cloud Platform (GCP) to manage and analyze terabytes of data every week. This data lake serves as a foundation for machine learning use cases, enabling the integration of advanced analytics and predictive modeling into the platform.

I assisted in setting up an automated MLOps pipeline to streamline the deployment, monitoring, and maintenance of machine learning models, ensuring efficient and consistent insight delivery.

To improve sales efficiency and enable more effective targeting by sales teams, I developed a scalable GCP-based data warehouse for handling large datasets and delivering real-time insights for marketing analytics. I enhanced user profiling and targeting strategies by integrating Google Analytics 360 and Salesforce Marketing Cloud. I implemented a PySpark-powered real-time streaming solution to optimize data processing and analysis workflows. These efforts led to a 20% increase in sales efficiency, a 15% boost in conversion rates, a 30% reduction in data processing time, and a 25% increase in marketing ROI, enhancing customer satisfaction and operational efficiency.

To enhance speech recognition accuracy and operational efficiency, I designed and implemented a GCP-hosted microservices platform for speech and recognition analytics.

The platform ensured secure and efficient resource access while integrating back-end services with analytics KPIs, such as user interaction metrics and speech analytics use cases. The integrations provided valuable data features, resulting in a 25% increase in speech recognition accuracy. By deploying optimized data workflows and pipelines on GCP, I reduced data processing time by 30% and accelerated model training cycles.

I collaborated closely with a data scientist and leveraged my expertise in data engineering, MLOps, and cloud infrastructure to deliver impactful solutions aligned with business objectives, driving growth and enhancing customer satisfaction.