Summary
Overview
Work History
Education
Skills
Timeline
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ABHISAI MOGILI

Arlington,Texas

Summary

Results-oriented Data Scientist with 10+ years of experience driving enterprise-scale AI and data solutions, with strong expertise in Machine Learning, Generative AI (GenAI), and advanced analytics. Proven ability to lead the full lifecycle of AI/ML projects—from design and development to deployment and optimization—across cloud-native ecosystems.

  • Led end-to-end GenAI solution development using Databricks, OpenAI, LangChain, and vector databases (Pinecone/FAISS), improving document search accuracy and reducing retrieval latency.
  • Built scalable Retrieval Augmented Generation (RAG) pipelines integrated with Delta Lake and Unity Catalog to support secure, governed enterprise LLM use cases.
  • Designed and deployed MLOps pipelines using MLflow, Databricks Workflows, and GitHub Actions, streamlining retraining cycles and enhancing model versioning.
  • Migrated large-scale data platforms from Snowflake to Databricks Lakehouse, reducing cloud costs and improving data pipeline efficiency for Fortune 500 clients.
  • Spearheaded “GenAI POC in a Month” accelerator, converting proofs-of-concept into production-ready AI solutions, accelerating client adoption.
  • Developed CI/CD automation for ML models and data applications using GitLab, Jenkins, and Terraform across hybrid cloud platforms (AWS, Azure, GCP).
  • Extensive hands-on experience with Spark, Kafka, PostgreSQL, MongoDB, and data lakes, optimizing batch and real-time processing pipelines.
  • Collaborated across engineering, DevOps, and analytics teams to deliver robust, reproducible ML workflows with high operational reliability.
  • Implemented governance and observability best practices using Prometheus, ELK Stack, and CloudWatch to ensure traceability, compliance, and performance.
  • Mentored junior data engineers and cross-functional teams, contributing to multiple elite recognitions as a Databricks service partner.

Overview

9
9
years of professional experience

Work History

Software Engineer

7-Eleven
03.2023 - Current
  • Led the development and deployment of machine learning models to optimize inventory management and stock tracking in real-time, reducing stockouts and overstock issues across thousands of stores.
  • Utilized Databricks to build scalable data pipelines, improving the efficiency of data processing for real-time inventory streaming and transaction tracking.
  • Designed and implemented Retrieval Augmented Generation (RAG) pipelines integrated with Delta Lake and Unity Catalog, enhancing data retrieval and decision-making across systems.
  • Built and maintained automated MLOps pipelines using MLflow and GitHub Actions to streamline model retraining and deployment, reducing manual intervention and improving time-to-market.
  • Migrated Seven-Eleven’s data processing infrastructure from Snowflake to Databricks Lakehouse, cutting data processing costs and accelerating pipeline execution for large-scale transactions.
  • Applied Generative AI (GenAI) techniques to generate personalized product recommendations, improving customer experience and driving higher sales in stores.
  • Leveraged Pinecone and FAISS vector databases to enhance search and retrieval performance, reducing document retrieval latency for inventory and product information.
  • Integrated Apache Kafka and Databricks to process and stream real-time data across inventory systems, ensuring accurate and up-to-date product availability across locations.
  • Developed data models and applied machine learning algorithms for predicting stock trends and automating reorder workflows, resulting in a more responsive inventory system.
  • Collaborated with cross-functional teams to design, develop, and deploy advanced AI-driven applications, improving operational efficiency and reducing manual tasks in inventory management.
  • Ensured data governance, security, and compliance by implementing industry-standard encryption, OAuth2, and JWT protocols across cloud-based applications and APIs.
  • Automated data pipeline workflows with Terraform and Databricks Workflows, enabling seamless integration of cloud-based services and improving operational scalability.
  • Utilized AWS services like Lambda, EventBridge, and SQS to automate notifications and event-driven tasks for inventory updates, vendor communications, and stock alerts.
  • Mentored junior data engineers, and collaborated with cross-functional teams to integrate machine learning models into the production environment, accelerating product deployment cycles.
  • Monitored and tracked model performance using Prometheus and Elasticsearch, providing real-time insights into system health, and ensuring high system reliability.
  • Contributed to Seven-Eleven’s recognition as a Databricks Elite Partner by delivering exceptional data solutions, driving client success, and supporting ongoing innovation in GenAI and machine learning projects.

Software Engineer

ABC Fitness
05.2016 - 02.2023
  • Developed and deployed machine learning models to optimize gym membership management workflows, enhancing member experience and improving operational efficiency.
  • Built and maintained data pipelines using Apache Spark and Databricks, automating the extraction, transformation, and loading (ETL) processes for gym membership data.
  • Utilized AWS services including Lambda, S3, and CloudWatch to implement scalable and cost-effective solutions for real-time membership validation and data processing.
  • Applied Generative AI (GenAI) models to personalize membership plans and promotional offers, improving user engagement and increasing membership retention rates.
  • Implemented Retrieval Augmented Generation (RAG) techniques using Delta Lake and Unity Catalog, enhancing customer-facing features by providing faster, more accurate membership-related information.
  • Utilized Pinecone and FAISS to build vector-based search solutions, enabling efficient retrieval of member data, and improving user experience through personalized recommendations.
  • Designed and deployed MLOps pipelines with MLflow, Databricks Workflows, and GitHub Actions to automate model retraining, ensuring continuous improvement of predictive models.
  • Migrated the company's data infrastructure to Databricks Lakehouse, improving data processing speed and reducing operational costs for large-scale membership data management.
  • Developed predictive models to forecast membership sign-ups, churn, and retention trends, providing actionable insights for marketing and operations teams.
  • Automated data workflows for member registration, subscription management, and real-time check-in validation, using AWS S3 and Lambda to ensure seamless operations across gym locations.
  • Applied machine learning algorithms to analyze gym attendance patterns, optimizing resource allocation and improving operational planning for peak hours.
  • Integrated Elasticsearch and Prometheus to monitor model performance and ensure that predictive models provided real-time, accurate insights into gym operations.
  • Collaborated with cross-functional teams to integrate machine learning models into the gym's digital platforms, enhancing user-facing applications and driving real-time engagement.
  • Utilized Terraform for infrastructure management, automating the deployment and scaling of data pipelines and machine learning models on AWS.
  • Designed and implemented a role-based access control (RBAC) system using OAuth2 and JWT, ensuring secure, compliant access to membership data and system features.
  • Contributed to the development of a custom recommendation engine for gym members, leveraging scalable vector search techniques and personalized recommendations to improve user satisfaction and engagement.

Education

Master of Science - Information Technology & Management

Webster University
San Antonio, TX

Skills

  • Databricks
  • Machine Learning
  • Generative AI (GenAI)
  • LangChain
  • Pinecone
  • FAISS
  • Retrieval Augmented Generation (RAG)
  • Delta Lake
  • Unity Catalog
  • MLflow
  • MLOps
  • CI/CD (GitHub Actions, Jenkins, GitLab)
  • Databricks Workflows
  • Snowflake to Databricks Migration
  • Python
  • Apache Spark
  • Apache Kafka
  • PostgreSQL
  • MongoDB
  • Vector Databases
  • Cloud Platforms (AWS, Azure, GCP)
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • AWS (S3, Lambda, EventBridge, CloudWatch)
  • Azure (Data Factory, Synapse)
  • GCP (BigQuery, Dataflow)
  • Terraform
  • Infrastructure as Code (IaC)
  • Containerization (Docker, Kubernetes)
  • Prometheus
  • ELK Stack (Elasticsearch, Logstash, Kibana)
  • Git
  • Postman
  • SQL/NoSQL Databases
  • CI/CD Automation
  • GitLab CI/CD
  • Data Pipeline Automation
  • Data Governance
  • Model Retraining Automation
  • Cloud Data Engineering
  • Distributed Systems
  • Data Lake Architecture
  • Big Data Processing
  • API Development
  • Real-time Data Streaming
  • Data Security & Privacy

Timeline

Software Engineer

7-Eleven
03.2023 - Current

Software Engineer

ABC Fitness
05.2016 - 02.2023

Master of Science - Information Technology & Management

Webster University

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