SOHAIL SHAIK

Results-driven Business Analyst with over 3 years of experience in data analysis, business process optimization, and digital transformation. Skilled in gathering and analyzing business requirements, mapping and testing processes, and delivering impactful solutions aligned with organizational goals. Proficient in leveraging data analysis tools such as SQL, Tableau, and Excel, with hands-on experience in ERP systems like PeopleSoft. Adept at collaborating with stakeholders, facilitating Agile methodologies, and driving organizational change to improve processes and outcomes. Recognized for strong analytical thinking, attention to detail, and effective communication, with a proven ability to navigate ambiguity and deliver value in dynamic environments.

Procure-to-Pay Process Transformation:

• Streamlined and optimized the Procure-to-Pay process, enhancing efficiency and improving stakeholder experiences.
• Gathered and documented business requirements in collaboration with Product Owners and Subject Matter Experts.
• Conducted gap analyses to identify and resolve process inefficiencies.
  Created detailed workflows, user stories, and decision logs for clarity across teams.
• Tested and validated process improvements, ensuring alignment with business goals.
• Delivered reports using SQL and Tableau to support data-driven decisions.
• Reduced inefficiencies through standardized processes.
• Enhanced decision-making with robust reporting and clear insights.

Sales and Inventory Optimization

• Optimized sales and inventory management through data-driven solutions, enhancing operational efficiency and reducing costs.
• Analyzed sales trends, inventory levels, and customer behavior using SQL and Tableau.
• Developed dashboards to monitor KPIs like sales performance and inventory turnover.
• Collaborated with teams to align data strategies with business goals.
  Automated reporting processes, reducing reporting time.
• Provided actionable insights that improved campaign ROI and reduced inventory costs.
• Boosted sales revenue through targeted insights.
  Improved stock management, minimizing overstock and stockouts.

Traffic Sign Recognition:

• Developed a Traffic Sign Recognition (TSR) system using YOLOv8 to improve real-time detection and classification of traffic signs for autonomous vehicles and Advanced Driver-Assistance Systems (ADAS).
• Implemented YOLOv8, leveraging its advanced deep learning capabilities for high-speed object detection. The model was trained and tested under varied conditions, including different lighting scenarios and partial occlusions, to ensure reliable performance.
• Achieved high precision and recall, demonstrating the model's robustness and effectiveness. The project contributed to enhancing the safety and efficiency of autonomous driving systems, with potential applications in integrating TSR with other sensory technologies.

Analyzing and forecasting IOWA liquor sales:

• Collected and analyzed real-time data from the IOWA state government website to forecast liquor sales.
• Conducted comprehensive time series analysis and developed models to predict future sales (in dollars), daily total volume purchased, and profit (in dollars).
• Implemented and evaluated multiple machine learning algorithms, including Linear Regression, Lasso Regression, Ridge Regression, Decision Tree Regressor, Random Forest Regressor, Gradient Boost Regressor, and XGBoost Regressor.
• Successfully identified the best-performing models for accurate forecasting, enhancing decision-making processes.