Urvinder Singh

- Technological Exploration Focus Group: Objective: Engage in focus group initiatives to identify AI/ML opportunities across end-to-end workflows, assess emerging technologies such as robotics, image analytics, and industrial drones, and foster strategic partnerships for innovative collaborations - Safety Parameter Detection using Computer Vision: Objective: Enhance on-site safety in manufacturing plants by monitoring adherence to safety regulations through advanced computer vision techniques. - Collection Analytics Objective: Leveraging advanced analytics methodologies to optimize collections processes, ensure timely commercial collections, and accurately assess customer credit limits and reducing the aging and DSO

Serving as a Visiting Faculty for Data Science/ Machine Learning for various edtech institutes 1- ExcelR 2- Boston Institute of Analytics 3- Staragile 4- FunctionUp 5- Imarticus 6- Emeritus 7- Career 247

Recommendation Engine: Project: Designed a sophisticated recommendation system specifically tailored for Modern Trade and Stand Alone Modern Trade chains. Outcome: Achieved significant upselling and cross-selling opportunities. Optimized shelf space allocation, leading to enhanced in-store product visibility and improved sales metrics. ------------- Go-To-Market Strategies Using Analytics: Project: Leveraged advanced analytics, particularly unsupervised learning techniques, to derive insights and shape strategic go-to-market plans for new/existing products. Outcome: Strategically expanded product presence in target regions, ensuring increased market penetration and revenue growth. ------------- Price and Promotion Recommendation System: Project: Developed a data-driven engine to recommend commercially viable pricing and promotion strategies, integrating market trends, competitor data, and consumer behavior insights. Outcome: Achieved a sustainable balance between competitive pricing and profitability, leading to increased market share without compromising revenue. ------------- Dynamic Route & Beat Planning Algorithm: Project: Conceived and implemented a dynamic algorithm for route and beat planning for sales and delivery teams. Outcome: Successfully increased sustainability by optimizing travel paths, significantly reduced operational costs, and generated incremental sales through efficient market coverage. ------------- POC Solutions for Marketing & Sales: Project: Collaboratively designed proof-of-concept solutions that incorporated advanced analytics to address marketing and sales challenges. Outcome: Enabled the marketing and sales teams to adopt data-driven strategies, resulting in improved campaign efficiency and increased sales conversions

1-5G KPI Time Series Analysis: Designed and implemented a neural network-based time series model to comprehensively analyze key performance indicators (KPIs) for 5G networks. This provided more profound insights into network efficiency and performance, facilitating data-driven decision-making. 2-Predictive Model for Call Drops: Spearheaded the development of a predictive model to anticipate call drops in the network. This proactive approach allowed management to formulate a strategic plan, reducing call drops and enhancing the end-user experience. 3-Faulty Node Pattern Recognition: Utilized K-means clustering to detect and identify patterns in faulty network nodes. This facilitated quicker diagnostics and corrective actions, leading to reduced downtimes. 4-Resource Allocation for Public Events: Devised an analytical solution to forecast the required number of telecom resources (e.g., sectors, radios, and sites) to adequately service large-scale public events like the Superbowl and Ultra Music Festival. This ensured optimal network performance during high-demand periods. 5-Telecom Site Engineer Feedback Analysis: Conducted comprehensive text analytics on feedback obtained from telecom site engineers. The insights drawn pinpointed reasons for the delay in issue resolutions. This analysis paved the way for streamlining processes and minimizing turnaround times for complaint resolutions. 6-Efficiency-Boosting Tools: Innovated and rolled out various tools geared towards augmenting efficiency in daily operations. These tools significantly reduced manual efforts, and error rates, and enhanced the productivity of the telecom delivery team.

1- Identify one or more reasons which may cause an outbreak of TB. Identifying these reason/s will further help to understand the impact of environmental conditions on the spreading of the disease. Tools/Techniques- Time Series, Neural Network, Big Query, SVM and Tableau 2-Developed a model on New York 311 complaints to predict number of complaints in a specified period along with the expected resolution time. This assisted the relevant department in manpower management. Tools/Techniques- Random Forest, Neural Network Time Series and Tableau.