Available to hire
Hi, I’m Ajaysimha Reddy Nallabapani, a Senior Data Scientist / ML Engineer with 5+ years of experience delivering AI-powered solutions across education, finance, and asset management. I specialize in GenAI, NLP, ML Ops, and cloud-native AI, building end-to-end systems that improve learning outcomes, automate decisions, and personalize experiences. I enjoy turning complex business problems into scalable, reliable AI pipelines and collaborating with cross-functional teams to drive measurable impact.
I’m driven by a strong focus on explainability, governance, and observability to ensure transparent, compliant AI systems. I embrace agentic AI, RAG, and knowledge-graph approaches to enhance decision making and automation, while keeping models robust through monitoring, drift detection, and continuous improvement.
Skills
Language
English
Fluent
Work Experience
Sr. Data Scientist / AI - Machine Learning Engineer (Python | NLP | GenAI | LLMs | Agentic AI | MLOps) at Tutorac Inc
January 1, 2024 - PresentDesigned and implemented AI-driven personalized learning solutions leveraging Generative AI, LLMs, and RAG pipelines to improve student engagement and course recommendations. Developed and deployed LLM-powered chatbots and AI tutors using OpenAI APIs, LangChain, CrewAI, and Copilot integrations, enabling automated Q&A, feedback analysis, and course guidance. Built Retrieval-Augmented Generation (RAG) pipelines with vector databases (Pinecone, FAISS) for contextual question answering and document search. Applied NLP techniques (text classification, sentiment analysis, NER) using Hugging Face Transformers, spaCy, and BERT/GPT models for analyzing student queries, feedback, and training materials. Engineered agentic AI workflows with CrewAI and LangChain Agents for orchestrating multi-step educational processes such as exam prep, content generation, and knowledge evaluation. Designed and trained deep learning models (CNNs, RNNs, LSTMs, Transformers) for demand forecasting, recommendation
Sr. Data Scientist / AI - Machine Learning Engineer (AI, NLP, Cloud ML & MLOps) at Cybage Software Pvt Ltd
October 1, 2021 - May 1, 2023Designed and deployed AI-driven predictive analytics systems for financial risk forecasting, customer segmentation, and behavior analysis using machine learning and big data frameworks. Collected, cleansed, and integrated structured and unstructured financial datasets from SQL databases, MongoDB, and market data APIs; automated ETL with AWS Glue, Azure Data Factory, and GCP Dataflow. Built customer churn, credit risk, and fraud detection models using Logistic Regression, Random Forest, Decision Trees, SVM, and ensemble methods, improving risk identification accuracy. Developed time-series forecasting models (ARIMA, STL, LSTM) for stock price prediction, market volatility, and investment behavior analysis. Applied NLP and deep learning techniques (spaCy, NLTK, PyTorch, TensorFlow, Transformers) for sentiment analysis of financial news, reports, and customer feedback, enhancing decision-making and product strategies. Implemented graph-based ML models for fraud detection and recommendatio
Data Scientist | AI - Machine Learning, NLP & MLOps | Python at Invesco
January 1, 2019 - September 1, 2021Designed, developed, and deployed data-driven applications using Python, Django, and Flask within an Agile-Scrum cycle. Built machine learning models for social network analysis, recommendation systems, fraud detection, and supply chain optimization using Scikit-learn, Pandas, and NumPy. Implemented NLP pipelines (tokenization, stemming, lemmatization, sentiment analysis) using spaCy, NLTK, and Transformers. Created and consumed REST APIs for ML model integration and real-time prediction services. Designed and optimized SQL/NoSQL queries across MySQL, PostgreSQL, and MongoDB for feature engineering and performance improvements. Developed time-series forecasting models (ARIMA, Prophet, LSTM) for financial analytics. Applied graph analytics for fraud detection and recommendation workflows. Built and managed end-to-end data pipelines, preprocessing structured/unstructured data for model training and deployment. Containerized ML applications using Docker & Kubernetes; deployed models on AW
Education
Qualifications
Industry Experience
Education, Financial Services, Software & Internet, Professional Services, Media & Entertainment
Skills
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