John S. Doss

The project involved assessing the maturity of the enterprise architecture and recommending steps to reduce cost by 30% and increase efficiency by 40% to meet rapidly evolving business needs. This included a roadmap of initiatives such as governance, API, microservices, change management, metrics, and cloud to align technology investments with business goals and objectives.

I assessed the operating model, organizational structure, application portfolios, data management, cloud strategy, DevOps, and security. I also reviewed and realigned IT organization and business interaction, redesigned customer channel workflows and capabilities for self-service and audience segmentation, and enhanced product catalog and inventory management systems to improve speed to market. Furthermore, I drove new revenue streams and application consolidations in ad fulfillment and invoicing, implemented data management and DevSecOps and security best practices, policies, and procedures, and implemented KPIs for maturity improvements. Finally, our team replaced and upgraded data interfaces for near real-time and real-time data availability and established a cloud center of excellence.

Sentiment analysis model for eCommerce and banking:
Explored customer sentiment in eCommerce using NLP and predicted banking product complaints
Skills: Sentiment analysis, NLP, eCommerce, banking

AI ecosystem and product recommendation:
Developed product recommendation engines and conceptualized data science ecosystems for effective AI implementation
Skills: Collaborative filtering, AI teams, data science ecosystem, team dynamics

Hotel reservation cancellation predictor:
Built a neural network model to forecast booking cancellations, aiding in business optimization
Skills: Neural networks, classification, hospitality, travel

AI product conceptualization:
Crafted a POC for an AI solution, including the problem statement, market analysis, and implementation timelines
Skills: AI applications, POC, market analysis, solution design

Targeted marketing for BFSI:
Used EDA and visualization to identify targets for bank marketing campaigns, deriving key insights for strategy formulation
Skills: EDA, visualization, BFSI

These projects spanned various sectors and showcased machine learning, data science, and business strategy use cases, demonstrating the balanced expertise needed in any AI implementation's technical and business facets.

The project involved a groundbreaking architectural overhaul for a government educational lending servicer. Faced with the limitations of a legacy mainframe, the goal was to align the organization's tech capabilities with its future business vision. A multi-disciplinary team combined expertise in mainframes, software architecture, cloud computing, cybersecurity, and business analytics.

After a detailed assessment, a hybrid cloud approach was adopted, leveraging AWS and Kubernetes for microservices orchestration. The project was executed in phases to minimize disruption, including setting up a cloud infrastructure, data migration, and deploying microservices. DevSecOps practices were also incorporated to maintain security standards.

The project achieved a 40% reduction in operational costs and improved system performance, agility, and security. The microservices architecture enabled faster deployments and updates, boosting time-to-market. It aligned with business goals, increasing stakeholder confidence. Advanced cloud security measures were implemented to protect against cyber threats.

The project served as a blueprint for modernization, showing the benefits of aligning technology strategy with business goals and capabilities.