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Hi, I'm Renuka Chintalapati, a passionate Data Scientist and Gen AI Engineer based in Durham, NC. I specialize in developing intelligent NLP systems, building scalable ML pipelines, and deploying cutting-edge AI solutions using advanced frameworks and cloud technologies. I love turning complex data challenges into actionable insights and impactful products. With a strong foundation in electrical engineering and hands-on experience across sectors like marketing analytics, healthcare, and education, I enjoy mentoring students and collaborating with cross-functional teams to push the boundaries of AI in real-world applications. Let's connect and innovate together!…Hi, I'm Renuka Chintalapati, a passionate Data Scientist and Gen AI Engineer based in Durham, NC. I specialize in developing intelligent NLP systems, building scalable ML pipelines, and deploying cutting-edge AI solutions using advanced frameworks and cloud technologies. I love turning complex data challenges into actionable insights and impactful products. With a strong foundation in electrical engineering and hands-on experience across sectors like marketing analytics, healthcare, and education, I enjoy mentoring students and collaborating with cross-functional teams to push the boundaries of AI in real-world applications. Let's connect and innovate together!

Renuka Chintalapati

Data Scientist, AI Engineer, AI Prompt Engineer, +1

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Hi, I'm Renuka Chintalapati, a passionate Data Scientist and Gen AI Engineer based in Durham, NC. I specialize in developing intelligent NLP systems, building scalable ML pipelines, and deploying cutting-edge AI solutions using advanced frameworks and cloud technologies. I love turning complex data challenges into actionable insights and impactful products. With a strong foundation in electrical engineering and hands-on experience across sectors like marketing analytics, healthcare, and education, I enjoy mentoring students and collaborating with cross-functional teams to push the boundaries of AI in real-world applications. Let's connect and innovate together!…Hi, I'm Renuka Chintalapati, a passionate Data Scientist and Gen AI Engineer based in Durham, NC. I specialize in developing intelligent NLP systems, building scalable ML pipelines, and deploying cutting-edge AI solutions using advanced frameworks and cloud technologies. I love turning complex data challenges into actionable insights and impactful products. With a strong foundation in electrical engineering and hands-on experience across sectors like marketing analytics, healthcare, and education, I enjoy mentoring students and collaborating with cross-functional teams to push the boundaries of AI in real-world applications. Let's connect and innovate together!

Available to hire

Hi, I’m Renuka Chintalapati, a passionate Data Scientist and Gen AI Engineer based in Durham, NC. I specialize in developing intelligent NLP systems, building scalable ML pipelines, and deploying cutting-edge AI solutions using advanced frameworks and cloud technologies. I love turning complex data challenges into actionable insights and impactful products.

With a strong foundation in electrical engineering and hands-on experience across sectors like marketing analytics, healthcare, and education, I enjoy mentoring students and collaborating with cross-functional teams to push the boundaries of AI in real-world applications. Let’s connect and innovate together!

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Data Scientist at SiriusMindShare LLC

June 1, 2024 - Present

Led the development of NLP systems to decode customer intent from 2,000+ marketing email subject lines using BERT-based models, shifting campaign strategy from intuition-led to insight-driven, improving click-through rates and reducing churn risk. Designed and operationalized a full ML lifecycle on Databricks using MLflow for experiment tracking and Jenkins/GitHub Actions for CI/CD, enabling the team to deploy and monitor new models 60% faster with no downtime. Delivered real-time inference through FastAPI and gRPC microservices on AWS Lambda, engineered for reliability, latency, and rollback safety to ensure decision-serving models.

Data Analyst at Wharton Business School

June 30, 2025 - July 18, 2025

Enabled high-confidence research attribution across 5M+ records by orchestrating ML-based matching agents using fuzzy logic and SVM validation, replacing error-prone manual processes with autonomous disambiguation at scale. Designed a multi-agent pipeline using LangChain and OpenAI to autonomously extract, verify, and enrich metadata for 800+ faculty profiles, eliminating multiweek verification cycles and embedding intelligence into institutional systems. Developed a task-driven RAG agent with FAISS to classify academic standing and roles, integrating structured insights into real-time leadership dashboards.

Marketing Analytics Intern at Sirius XM

August 31, 2023 - July 18, 2025

Built predictive models with XGBoost achieving 89% accuracy to identify at-risk subscription users, enabling proactive retention campaigns. Improved campaign strategy with scalable controlled A/B tests, surfacing behavioral lift and conversion impact across customer segments. Automated behavioral data pipelines using Python and GCP BigQuery, delivering insight-driven Tableau dashboards for ongoing optimization to operational teams.

Data Scientist at Infozion Technologies

June 30, 2022 - July 18, 2025

Developed a BERT-powered chatbot for BMW improving customer support resolution speed by 40% and increasing satisfaction to 85%. Deployed production-grade NLP pipelines using TensorFlow and RASA, containerized with Docker and orchestrated via Kubernetes for high-volume live user interactions. Collaborated with engineering, product, and customer ops teams to transform support patterns into structured intents, enabling real-time feedback loops and data-driven escalation flows.

Data Science Intern at Hindustan Petroleum Corporation Limited

April 30, 2020 - July 18, 2025

Developed time series ML models for predictive maintenance improving failure detection accuracy by 25%. Automated reporting and monitoring workflows integrating SQL with Tableau dashboards to enable faster, data-backed servicing decisions. Delivered early alerting capabilities to reduce unscheduled maintenance events, supporting operational efficiency and cost control at plant-level workflows.