Revanth Kumar Gonuguntla
Data Scientist - AI/ML • g*********************@gmail.com • +15******240 • drivetube.ai/•••••
Professional Summary
Data Scientist - AI/ML with 6+ years of experience managing end-to-end ML lifecycles, building MLOps pipelines, and deploying GenAI/LLM solutions. Experienced in model development, production deployment, monitoring, and cross-functional collaboration across telecom and financial domains.
Technical Skills
Programming Languages: Python,R
Frameworks and Libraries: TensorFlow,PyTorch,scikit-learn,XGBoost,LangChain,Matplotlib,Seaborn
Databases: SQL,Snowflake,BigQuery,AWS Redshift,MySQL,MongoDB
Cloud and DevOps: AWS,Azure,GCP,Docker,Kubernetes,Azure Kubernetes Service,Google Kubernetes Engine,Jenkins,Azure DevOps,AWS CodePipeline,Terraform
Data and Analytics: Apache Spark,PySpark,Apache Airflow,Databricks,AWS Glue,Azure Data Factory,DBT,Databricks Feature Store,Microsoft Fabric,Palantir Foundry,Power BI,Tableau
Tools and Methodologies: Hugging Face Transformers,OpenAI,LlamaIndex
Retrieval & Vector Stores: FAISS,Pinecone
MLOps & Model Management: MLflow,DVC,Azure ML,AWS SageMaker
Streaming & Messaging: Apache Kafka,Azure Event Hubs,Pub,Sub
Monitoring & Observability: Grafana,Splunk,ELK Stack,AWS CloudWatch,Azure Monitor
Work Experience
AT&T
Dallas, TX
Data Scientist - AI/ML
JAN 2025 – Present
Worked on AI/ML for telecommunications: network telemetry, logs, and device metrics to enable anomaly detection, threat intelligence, and predictive maintenance.
Tech Stack: TensorFlow, PyTorch, scikit-learn, Apache Airflow, Databricks, Azure Data Factory, Apache Kafka, Spark, Azure ML, AWS SageMaker, Databricks Feature Store, Snowflake, Hugging Face, LangChain, OpenAI, Microsoft Fabric, Palantir Foundry, Kubernetes, Docker, MLflow
- Designed and deployed ML models for network anomaly detection and predictive maintenance using TensorFlow and PyTorch, reducing unplanned downtime and improving fault detection coverage.
- Built automated ETL pipelines with Apache Airflow, Databricks, and Azure Data Factory to process large telemetry and log datasets, cutting manual data processing time by 40%.
- Implemented real-time streaming analytics with Apache Kafka, Spark Streaming, and Azure Event Hubs to enable low-latency threat detection and operational alerts.
- Integrated LLMs and GenAI workflows (Hugging Face, LangChain, OpenAI) to automate network documentation and intelligent alert summarization, lowering support team workload by ~30%.
- Managed feature engineering and storage using Databricks Feature Store and Snowflake; applied time-series models (Prophet, ARIMA, LSTM) to forecast capacity and optimize maintenance schedules, reducing operational costs by 10%.
- Enforced data governance and security for sensitive network datasets using Microsoft Fabric and Palantir Foundry; deployed models via Azure ML, SageMaker, and Kubernetes with CI/CD for reproducible production rollouts.
Global Atlantic Financial Group
Buffalo, NY
Data Scientist - AI/ML
FEB 2024 – DEC 2024
Delivered ML and GenAI solutions for financial services: predictive maintenance for machinery data, customer churn, fraud and document analysis for investment and compliance workflows.
Tech Stack: scikit-learn, TensorFlow, LangChain, Hugging Face, LlamaIndex, AWS Glue, Databricks, Snowflake, AWS SageMaker, Kubernetes, AWS Redshift, Athena, Apache Spark, Kafka, DBT
- Developed churn prediction and credit-risk models using scikit-learn and TensorFlow; improved model accuracy by 25% through feature engineering and hyperparameter tuning.
- Built RAG-based financial document analysis pipelines (LangChain, Hugging Face, LlamaIndex) integrating market data to enable context-aware risk assessment and regulatory summarization.
- Designed and deployed Generative AI solutions to produce financial summaries and automated market reports, supporting portfolio teams and reducing manual reporting effort.
- Implemented ETL and data governance workflows with AWS Glue, Databricks, and Snowflake to standardize financial data and improve downstream model reliability.
- Engineered real-time ML inference pipelines on AWS SageMaker and Kubernetes to deliver low-latency financial predictions for fraud detection and trading signals.
- Developed recommendation systems using collaborative filtering and matrix factorization to increase customer engagement by ~30% and supported A/B testing for feature rollouts and model validation.
Tata Consultancy Services
Hyderabad, Telangana
Data Scientist - MLOps
March 2020 – AUG 2023
Delivered MLOps and production ML capabilities for enterprise clients; focused on model lifecycle automation, monitoring, IaC and containerized deployments across AWS/Azure environments.
Tech Stack: AWS SageMaker, AWS EC2, AWS S3, CloudFormation, Terraform, Docker, Kubernetes, Jenkins, Azure DevOps, MLflow, DVC, PySpark, Databricks, XGBoost
- Orchestrated end-to-end MLOps pipelines integrating training, versioning, and deployment for multiple ML models using AWS SageMaker, Docker, and Kubernetes.
- Implemented CI/CD for ML workflows with Jenkins, CodePipeline, and Azure DevOps to automate testing, packaging, and production rollouts, improving deployment consistency.
- Built monitoring and model-health solutions using MLflow, logging, and alerting frameworks to detect drift and performance regressions, enabling proactive retraining.
- Applied Infrastructure as Code (CloudFormation, Terraform) to provision repeatable cloud environments and reduce environment setup time for data science teams.
- Developed and deployed supervised models including XGBoost and neural networks; executed feature engineering and EDA at scale using PySpark and Databricks.
- Established model versioning, reproducibility, and rollback processes using Git, DVC, and MLflow; collaborated with cross-functional teams to align MLOps practices with business SLAs.
Powered by Drivetube · Create your own profile at drivetube.ai
Explore Drivetube
- Drivetube Profile — your free digital resume — at drivetube.ai/in/your-name: one true standard resume with a Hiring Snapshot (visa status, expected salary, notice period, work preference, relocation), an ATS-ready PDF download and a single shareable link. Free forever; interview requests come from verified employers and your contact details stay masked until you accept. Documentation.
- Free Job Board — verified openings crawled ATS-by-ATS from 100,000+ real company career pages across 35 ATS platforms. Shows the true posting date from the source ATS — not when a listing was indexed — and deletes every general listing 3 days after it was actually posted. No ghost jobs, no ad-sponsored listings, no staffing reposts, no account needed. Documentation.
- Job Hunt Program — managed job hunting, a one-time purchase from $199.99. JobScout matches verified roles to your real experience band, Blend AI writes a uniquely tailored resume and cover letter for every application, and the Autofill extension fills the form — or Let Us Apply submits it for you. Documentation.
- Resume Writing Services — human-written, ATS-optimised resumes by senior career writers, from ₹499.99 / $25.99. Available in every country, written to the destination country's own standard — a US resume, UK CV, German Lebenslauf and Indian resume are genuinely different documents. A paid service, separate from the free Drivetube Profile. Documentation.
- Community Membership — from $4.99/month (₹1,999/year in India). Unlocks the gated job-board filters — visa sponsorship, security clearance, workplace and application time — plus Job-Scout AI matching, Resume Report AI, Interview AI prep sheets, Recruiter Outreach AI sent from your own Gmail, Apply or Skip triage, a daily market feed and a $10,000+ library including 23 ATS-validated resume templates. Documentation.
- Drivetube Hire — for employers — hiring with no job postings and no applications. Paste your real job description and AI matches it against candidates' true standard resumes, returning ranked candidates with a match %, matched and missing skills and written reasoning. Free tier included; employers pay, candidates never do. Documentation.
Full product documentation — every product explained, with feature-by-feature comparisons against the job boards, AI apply tools, resume services and hiring platforms people actually use.
The job board covers the United States, India, United Kingdom, Canada, Europe and Australia, and Resume Writing Services are available in every country.