Bhisham Sharma

Responsibilities and Contributions: • Led the Healthcare Data Quality and Governance Project for Eli Lilly, overseeing data from multiple domains including customers, patients, and activities. • Directed the team in establishing end-to-end data governance from onboarding to consumption, ensuring compliance and business relevance. • Supervised validation of Data Transfer Agreements (DTAs) using LLM-based NLP models to assess data usage and compliance terms. • Designed and implemented automated AWS pipelines for data validation, metric computation, and anomaly detection. • Managed integration of data pipelines with RDS, Redshift, and Aurora, enabling centralized metric storage and analysis. • Guided the creation of interactive dashboards in Power BI and Quicksight for various personas such as business owners, stewards, and facilitators. • Coordinated communication with vendors, business stakeholders, and data teams to resolve quality issues and implement corrective actions. • Applied machine learning and statistical analysis for anomaly detection and data integrity monitoring. • Utilized Python 3, AWS Glue, Lambda, CloudFormation, Redshift, Aurora, SageMaker, Power BI, Quicksight, GitHub, Machine Learning, NLP, and LLM-based document analysis. • Managing a high-impact Ecommerce Analytics project for a US-based client, overseeing end-to-end delivery and stakeholder engagement across multiple business units. • Collaborating with cross-functional stakeholders to gather, analyze, and translate business requirements into technical deliverables. • Bridging the gap between business and IT teams to ensure alignment of objectives, timelines, and expectations. • Leading Agile project management using JIRA — prioritizing tasks, tracking progress, and ensuring timely delivery of milestones. • Coordinating with IT teams and business owners to identify and resolve blockers, ensuring smooth execution of project sprints. • Driving the development of a multi-tenant Ecommerce Analytics Platform on AWS, enabling customer onboarding, sales insights, and data orchestration. • Conducting project and data discovery, schema design, and integration mapping across platforms such as Kroger, DoorDash, Amazon Vendor Central, Instacart, and Walmart. • Architected the end-to-end system design and data model for the analytics platform leveraging AWS services. • Leading product, DevOps, MLOps, frontend, and backend teams — utilizing technologies including Python, AWS, DBT, MinIO, Adminer, PostgreSQL, React, Terraform, and Pulumi. • Mentoring team members in backend schema design and ensuring adherence to scalable and secure architectural principles. • Managing source control and CI/CD pipelines using GitLab, ensuring consistent deployment practices and efficient collaboration. Business and Productivity Impact: • Established a comprehensive Data Quality and Governance Framework that standardized validation, auditing, and monitoring across multiple healthcare data domains, ensuring accuracy, compliance, and trust in enterprise datasets. • Led end-to-end requirement gathering, stakeholder alignment, and data auditing processes, creating a structured foundation for scalable analytics and reliable business insights. • Directed cross-functional project and technical teams, fostering collaboration between data engineers, analysts, and business owners to accelerate delivery and maintain data integrity. • Implemented automated AWS-based pipelines for data validation, metric computation, and anomaly detection, reducing manual oversight and improving reporting efficiency. • Built a culture of continuous quality improvement through clear documentation, defined data ownership, and real-time quality metrics available via Power BI and Quicksight dashboards. • Enabled faster, more reliable decision-making for business users by ensuring high-quality, well-governed data pipelines supporting sales, patient, and operational insights. • Combined strong project leadership with technical depth in Python, AWS, and analytics to deliver sustainable, compliant, and business-aligned outcomes.

Responsibilities and Contributions: • Led the development of a real-time AI forecasting system for Crescent Petroleum to predict amine foam formation 30 minutes in advance. • Implemented Adaptive RNN, LSTM, and GRU models to handle dynamic, non-seasonal time series data. • Delivered an end-to-end solution covering data ingestion, model training, and Azure ML deployment. • Directed the creation of a multilingual QnA bot for ITC, enabling MSMEs to query trade data in multiple languages. • Supervised prompt engineering, token optimization, and SQL query generation for complex data sources. • Integrated Azure OpenAI, Translation Services, Flask API, and Redis Indexer for scalable performance. • Led the design of an AI-driven Organizational Data Discovery Tool to fetch employee insights from Azure SQL. • Built and deployed a KPI Bot to convert natural language into complex SQL queries across multiple tables. • Headed the development of Etisalat CC Bot using Azure OpenAI and Bing API for real-time web information retrieval. • Utilized Python 3, Azure Services, Prompt Engineering, and NLP techniques across all projects. Business and Productivity Impact: • Successfully led and delivered the Proof of Concept, leading into potential client conversion that brought business to the company • Saved the LLM token cost by 7% by fine tuning the prompt and applying text pre processing techniques • Devised a runtime snippet extraction method to replace full-site scraping, improving latency by 20%.

Responsibilities and Contributions: • Worked on the Virgin Media Ireland Project, focused on telecommunications and internet services for wholesale and retail customers. • Developed Python-based orchestration logic for Customer Facing Services (CFS) to handle and fulfill customer requests. • Implemented product validation and catalog management workflows within the service inventory system. • Built and tested REST API services to integrate with backend systems and ensure seamless service delivery. • Utilized tools and technologies including Python 3, REST API, Blue Planet, Postman, Jira, Confluence, Mobaxterm, Docker, and GitHub. Business and Productivity Impact: • Increased delivery rate and number of orchestrations by 3%, enabling leaders to focus on further growth plannings

• Worked as a Python AI/ML and Backend Developer at Quy Technologies Pvt. Ltd. on a 3-month contract (Oct–Dec). • Developed an AI driven cryptocurrency web application from concept to deployment. • Designed and implemented the entire backend system using Django. • Built and optimized forecasting models using LSTM neural networks for crypto price prediction. • Integrated data pipelines and REST API to support real-time analytics and model serving. Business and Productivity Impact: • Achieved increased response rate by 4% from hosted forecasting models by optimizing async tasks and web sockets code

• Developed and maintained RESTful APIs using modern Python frameworks such as Flask and Django. • Performed feature engineering, data analysis, and visualization using libraries like Matplotlib and Seaborn. • Built and deployed machine learning and neural network models for predictive analytics. • Designed and managed data ETL pipelines, including data transformation and validation processes. • Utilized Microsoft Azure services for application development and deployment. • Implemented and maintained projects using various AWS services for cloud-based operations. • Mentored college students in Python and Java, assisting them with their final thesis and capstone projects.

Microsoft Certified: Azure Data Scientist Associate

Microsoft

Microsoft Certified: Azure Fundamentals

Microsoft