Driving Engineering Innovation in Workforce ManagementAs Vice President of Research and Development , I spearhead the creation and evolution of our comprehensive Workforce Management suite of products. My role is pivotal in shaping the future of retail operations through cutting-edge technology solutions.Leading a dynamic team of over 60 engineers , Data Scientists , mathematicians , I oversee the development of critical components including Labor Planning, Standards Management, Time Series Forecasting, Scheduling, Time and Attendance, Task Management, and Mobility products. I work on products and solutions that empower Fortune 500 retailers worldwide to optimize store operations, enhance workforce efficiency, and achieve unprecedented levels accuracy in inventory management through UPC Forecasting.A key focus has been modernizing the forecasting architecture to significantly enhance scalability and performance. By implementing advanced technologies and methodologies, we've achieved substantial improvements in handling large-scale data sets and delivering accurate forecasts with increased speed. Additionally, I've been instrumental in driving the adoption of CI/CD practices across the product portfolio. This strategic shift has resulted in accelerated development cycles, improved product quality, and greater overall efficiency.In addition to fostering a culture of innovation within the engineering organization, I collaborate closely with cloud and IT teams to ensure seamless deployment and support of our products across diverse global markets. My commitment lies in delivering robust and scalable solutions that drive tangible business value for our clients.

Suvarna's work at Groktech AI focused on using AI to address specific challenges faced by various industries. During my tenure consulting at an e-commerce micro-service delivery company as part of Groktech, we had the pleasure of working with them on a project developing a promise time prediction AI service specifically tailored to the needs of a world-wide ecommerce Jewellery chain. The ability to accurately predict promise times can be a significant advantage in today's competitive landscape. Groktech was able to deliver a service that predicted the promise dates with 98% accuracy to the actual ship dates. The AI service we developed aimed to:* Increase Efficiency: By leveraging historical data and machine learning algorithms, the AI could predict promise times with greater accuracy, allowing for better resource allocation and improved delivery timelines. We were able to predict these with about a 98% accuracy across all the retail locations of the specific retail chain. * Enhance Customer Satisfaction: More accurate promise times could lead to a more transparent and reliable customer experience, fostering trust and loyalty.* Optimize Operations: With a clearer picture of delivery timelines, Our client could optimize its internal processes and streamline operations.Suvarna's engineering leadership in these area has helped Groktech AI become a valuable partner for retail software companies. By applying AI to these specific problems, Groktech AI is helping retailers improve their efficiency, profitability, and customer satisfaction.Check out https://groktech.ai/services for more information on the various products and services at Groktech.

A member of the Harvard Business Review Advisory Council, an opt-in research community of business professionals. As an Advisor, I will provide insight to shape the content developed and provide my perspective on ideas from HBR and the wider world of management and leadership.

As Director at Zebra Technologies, I have contributed to building products , models and technology enhancements within Zebra software products that have helped Zebra Workforce Management expand into the banking vertical and increase its CARR by over ~$20M since 2018. As Director of Engineering I Design, Develop and Manage the Engineering processes for the Retail software solutions at Zebra specializing in Predictive forecasting and AI Budgeting applications. I've invented new forecasting methodologies for :1. Best fit time-series forecasting techniques2. Anomaly/marker impact analysis3. Weather and seasonality impacts. I am responsible for the design and development of Enterprise Forecasting Applications, based on a combination of Statistical models and advanced Ensemble models for Workforce Optimizations engines. Cloud Computing:Google CloudGoogle KubernetesSaas Distributed computing using Webshepere, DB2 & Apache SparkGoogle Cloud SQLMy other areas of interest include:1. Generative AI Technology - AI Art Technology and its applications. 2. Blockchain Technology - I have invented methodologies to track shipments & returns for various supply chain management systems using smart contracts in a blockchain.Worked with the APP-CAIR (Centre for Artificial Intelligence Research) at BITS Pilani on a collaborative lab pilot, to put together Machine learning and AI products that would solve real world problems related to retail AI.Worked on NBEATS implementation for retail timeseries forecasting with a team of undergraduate students , faculty members under the supervision of Dr. Ashwin Srinivasan (Senior professor of Data Science and Artificial Intelligence)Worked on Telos and Hyperopt methodologies for hyperparameter tuning generalization for various algorithms including Genetic Algorithm and ML Algorithms. Worked with the project team that implemented Ripple down rule based anomoly detection on retail time keeping and payroll data.

Manage engineering design and development of predictive analytics in workforce scheduling.1. Design and Manage Development of advanced machine learning Algorithms for Predictive Forecasting for Retail Workforce metrics (Using Spark ML APis) . 2. Interpret and present modeling and analytical results to non-technical audience . 3. Compile complex predictive model packages for production deployment. 4. Define financial and analytical metrics to measure development and production outcomes and produce performance reports for various algorithms developed and assess the best methodology based on the industry/market standards . 5. Propel analytic product development via conducting statistical analyses on various data sources . 6. Conduct transaction data analyses with big data technologies such as Spark and Hadoop for internal and external product owners, and develop deeper insights into the products using advanced statistical methods . 7. Support sales and marketing efforts with sound statistical analysis of data and calculate performance indicators and accuracy indicators for the predictions while using various types of predictive Machine Learning and mathematical Forecast models . 8. Execute ad-hoc analyses to meet the fast-changing market demandsDevelop business requirements and appropriate statistical analysis/prototypes to meet critical business needs . 9. Work on cross functional teams and collaborate with internal and external stakeholders

1. Manage the entire product line implementation life cycle from strategic planning to tactical activities for Reflexis Workforce scheduler and Analytics.2. Specify market & customer requirements for current and future products by conducting market research supported by ongoing visits to customer’s locations.3. Drive solution set across to the Engineering teams through market requirements, product contract, and positioning.4. Recommend the nature and scope of present and future product lines by reviewing product specifications and requirements from various customers and prospects.5. Work with the VP - Product implementation and SVP Engineering, to come up with strategic customizations that will help with overall product improvement, customer satisfaction and quality control.6. Manage and perform Functional stress test and assess/Improve scalability of the product by analyzing the test results, and suggest infrastructure-scaling plans.7. Assist with Pre-sales activities by delivering product customization that will provide an edge in building product sales strategies.8. Maintain product management staff by recruiting, orienting, and training employees.9. Maintain product management staff job results by counseling employees; planning, monitoring, and appraising job results.

1. Analyze requirements, pre-sales activities, implementation kickoff 2. Define Solution scope and Identify gaps between the customer business functions and solution design.3. Provide custom solutions in line with the requirements and redefine product scope, to ensure integrity of the software product.4. Create sequence diagrams, use-case diagrams, functional specifications, functional algorithms, user interface design and functional pseudo-codes necessary for engineering and data model design.5. Finalize functional specification and Data model design to bridge gaps between the software solution and the business requirement.R&D Team: Design, develop and implement the task manager solution software on the IPAD and the IPHONE platform. I also spent 2 months in India training the Research and Development team on Apple IOS programming.1. Mobile Adaptive Labor Scheduling – Feed, Design and Implementation of User Interface - (prototype development)2. Task Manager on IPAD – Implementation and Rollout.3. Action Box UI – Design and Implementation– Adaptive Labor Scheduling. (prototype development)

1. Manage a team of 8 engineers and contributed towards building various algorithms and programs in JAVA using MVC architecture on J2EE platform, specific to various modules of the Workforce management (WFM) product.2. Worked on optimized database queries (oracle, MYSQL, Microsoft SQL Studio) that ensure scalability and perform business functions that are critical.3. Worked with my team to maintain and performed enhancements to code modules.4. Worked with the quality assurance team to ensure compatibility of the product on multiple application servers and webservers such as Apache tomcat, IBM Websphere, Glassfish etc.5. Ensure compatibility of SQL queries on multiple databases such as Oracle, Microsoft SQL, and MYSQL etc.6. Oversee the design & development of the entire Reflexis scheduling dashboard module.7. Oversee the design and development of various modules such as Dynamic line schedule, forecasting.

1. Participated in the full life cycle of a project including, Business Analysis, Functional Specification, System Configuration, Design, Testing2. Worked on Application and database server installation maintenance and tuning for sandbox environments. 3. Learned the capabilities and limitations of various Workforce Management software offerings and applied this knowledge on enhancing the product functions.4. Researched, documented, configured and tested all functional elements involving rules and policies5. Developed and documented testing strategies, using App perfect.6. Collaborated with the Engineering team to ensure the functional specifications are communicated and customized in the product.

Was part of the Center of excellence laboratory focusing on Research and development center for Workforce management in Chennai India.Was involved in doing operation and market research on retail domains to improve the scheduling and the forecasting algorithms used in the WFM Product.Programmed various aspects of forecasting and came up with the best fit algorithms for various sectors of retail and the dynamic line schedule which was one of a kind in the market at the time.

Hedge Fund Administration Tool Development - Geneva Development

Worked On Asset tracking System for the Company using an Internal Tool called Performa Studio. The back end was coded in Core Java and Oracle DB was used.