• Led and managed a team of data scientists, data analysts, and data engineers in developing and implementing data strategies to drive business objectives.• Collaborated closely with cross-functional teams, translating statistical and machine learning knowledge into actionable insights and product applications.• Defined the vision for data transformation, machine learning training and inference platforms, ensuring data quality and end-to-end MLOPs implementation.• Mentored and developed team members, fostering a culture of innovation, continuous learning, and best practices in data science and data engineering disciplines.• Managed multiple data science and data engineering projects, allocating resources, and ensuring on-time delivery of high-quality results.• Partnered with stakeholders to identify new opportunities, leveraging data-driven approaches to optimize marketing campaigns and customer experience.• Presented findings and recommendations to senior executives and key stakeholders, influencing business strategies and driving data-driven decision-making.• Designed patterns for different architectures, components for multiple use cases.

• Speech Recognition System: Developed a robust speech recognition system (ASR) through extensive data processing and transfer learning techniques, significantly enhancing product effectiveness and accessibility. Employed a simple speech detector tailored for voice interfaces, trained on a diverse dataset featuring over 30 distinct short words and sounds sourced from thousands of different origins. Leveraged advanced Mel-frequency cepstral coefficients (MFCCs) for optimal performance.• Optical Object Recognition System and Cognitive Platform: Spearheaded the creation of an advanced optical object recognition system (OCR) alongside text summarization, classification, topic modeling, and sentiment analysis capabilities within a cognitive platform using KNIME. Implemented across various product and service domains, this platform facilitated the analysis of marketing strategy effectiveness and customer feedback, empowering data-driven decision-making processes.• Information Retrieval System: Engineered an information retrieval (IR) system tailored specifically for financial reports, enabling efficient and accurate extraction of critical insights from complex financial data. Utilized NLP techniques to streamline access to relevant information, enhancing decision-making processes within financial contexts/forms/tables.• Model Monitoring and Enhancements: Provided mentorship and conducted in-depth investigations to enhance underperforming models, ensuring optimal performance and accuracy across various applications. Leveraged analytical expertise to identify and address areas for improvement, driving continuous refinement and optimization of machine learning models.

• Customer Segmentation Model Development: Spearheaded the development of advanced customer segmentation models tailored to identify prospective buyers for new and used vehicles across various brands, including initiatives related to new product launches. Leveraged sophisticated analytical techniques to dissect customer data and unveil actionable insights, driving targeted marketing strategies and sales initiatives.• Cross-Buy Model Development: Orchestrated the creation of cross-buy models catering to diverse segments such as luxury, non-luxury, full-size, mid-sized, and sports categories. Employed predictive analytics methodologies to uncover cross-buying patterns and behaviors, facilitating strategic decision-making and maximizing revenue opportunities across different product lines.• Model Investigation and Enhancement: Conducted thorough investigations and enhancements of existing predictive models, achieving a remarkable 40% improvement in accuracy. Applied analytical rigor and innovative approaches to identify and rectify performance deficiencies, ensuring models align with business objectives and deliver actionable insights.• Process Improvement and Automation: Drove process improvement initiatives aimed at shortening execution cycles and enhancing efficiency through the implementation of automation solutions. Leveraged macros, parallel processing techniques, and virtual machines to streamline workflows and optimize resource utilization, resulting in significant time and cost savings.• Scoring Process Optimization: Led efforts to enhance the scoring process for vast datasets, reducing job cycle times from 16 hours to a mere 6 minutes. Implemented optimizations and efficiency enhancements to accelerate data processing and analysis, enabling faster decision-making and real-time insights delivery.