Mohammed Husain

• Designed and deployed machine learning models using Python frameworks (Scikit-learn, PyTorch, TensorFlow) and optimized them for production.• Developed interactive Plotly dashboards and implemented big data processing with Python and Spark to support product analysis and decision-making.• Streamlined end-to-end workflows, including data engineering, model deployment, and product design, for data-driven business solutions.• Built and deployed scalable ETL pipelines, Flask APIs, and Streamlit applications o

• Designed and developed an ML model for vendor-level and item-level matching. • Created an ML model to estimate and forecast user numbers, enhancing predictive analysis and strategic planning. • Designed and maintained interactive dashboards in Tableau for stakeholders, delivering real-time insights and facilitating data-driven decision-making. • Built and managed data pipelines, performing ETL processes using Google BigQuery and Google Colab Notebooks to ensure seamless data integration and processing.

• Conceptualized and implemented an advanced pipeline model automating the generation of monthly, quarterly, and weekly reports, managing 2000+ data points and tracking 140+ critical business metrics. • Significantly enhanced operational efficiency by reducing manual labour by over 40 hours per reporting cycle, mitigating human error, and streamlining processes • Engineered robust database pipelines to seamlessly extract data from Redshift and transfer it to local environments using Python and Excel sheets.

• Developed and deployed an ML Publisher Recommendation model using K Means Clustering on Azure platform. • Achieved a notable 33% month-on-month increase in advertiser-publisher invitations through the Recommendations tab on the website, along with an 8.36% monthly rise in total invitations. • Leveraged Python, PySpark, and Pandas within Azure Databricks to analyze vast datasets and develop actionable insights.

• Directed the Project Development Cycle from Requirement Analysis to Deployment, ensuring stakeholder alignment and project success. • Engineered a pioneering Product Availability Machine Learning Model, leveraging advanced techniques in Python, SQL, and Azure tools, yielding significant business impact. • Applied cutting-edge video and image processing techniques to drive actionable insights and optimize project outcomes.

• Developed a Video Analysis POC using YOLO and implemented ML models for Image and Video classifications, showcasing expertise in advanced analytics and Image/Video Processing. • Specialized in Image and Video Processing techniques including Face Detection and VoTT Tagging Tool, contributing significantly to project success and demonstrating advanced analytics capabilities.