Satyanarayana Repala
Senior Data Scientist - Level 3
Bengaluru
Summary
Experienced data scientist with a strong background in fraud detection, recommendation systems, visual search, and natural language processing (NLP). Skilled in both classical machine learning and deep learning techniques. Led projects to stop fraud and account takeovers, and built smart systems that recommend products and understand images or text. Good at working with cross-functional teams, bringing in third-party models, and making sure models are accurate, fair, and well-governed. Also experienced in using large language models (LLMs) to find trends and help businesses make better decisions.
Overview
9
9
years of professional experience
6
6
years of post-secondary education
1
1
Certification
4
4
Languages
Work History
Senior Data Scientist Level 3
Morgan Stanley
04.2024 - Current
- Leading a team of 3 data scientists focused on fraud detection, particularly Account Takeover (ATO) prevention.
- Generated features and business rules to block suspicious logins, transactions, and user activity in real time — covering areas like cookie spoofing and social engineering.
- Onboarded vendor models for identity document verification and Early Warning Signals (EWS) for deposit checks during customer onboarding.
- Serve as Model Specialist responsible for evaluating model performance and maintaining Model Risk Management (MRM) documentation.
- Worked on an Auto Encoder-based fraud detection solution to capture behavioural patterns and detect anomalies in user activity sequences and device changes.
- Leveraged Large Language Models (LLMs) to build an interactive system that highlights current fraud trends and patterns for easier analysis.
Senior Data Scientist Level 2
Condenast India
09.2021 - 02.2024
- Developed personalized recommendations using Graph Neural Networks in PyTorch for media industry.
- Created an open-text fashion image search system using SAM and CLIP architectures, enabling text-based searches across one million images.
- Built performance monitoring dashboards for model assessment.
- Lead projects on lifeline packages and subscriber lifetime value (LTV) estimation using LSTM models and engagement data.
- Identified high-value subscribers through precise LTV estimation.
Data Scientist
IOPEX TECHNOLOGIES
03.2019 - 09.2021
- Invoice Parameter Extraction: Automated extraction of invoice parameters using image processing and NLP (NER models), improving data accuracy and operational efficiency.
- Employee Performance Monitoring System: Developed a system to classify user screen recordings, enabling better employee performance tracking and data-driven management decisions.
- Email Intent Detection System (Salesforce Integration): Built a model to detect email intents such as complaint, feedback, query, and compliment, seamlessly integrated with Salesforce for improved customer response and workflow automation.
Software Engineer
Tata Consultancy Services
06.2016 - 03.2019
- Retail store shelf compliance detection model, ensemble model with object detection, feature extraction, text extraction from products, and identify the product.
- End to End API integration and deployment onto AWS E2 instance
- Worked as support engineer for 1 year for client Morgan Stanley.
Education
BE - Electrical And Electronics
SASTRA UNIVERSITY
Tanjore 06.2012 - 06.2016
High School Diploma -
Vignan Junior College
Guntur 06.2010 - 06.2012
Skills
- Machine Learning(LR,SVM,bagging and boosting)
- Deep Learning (CNN, LSTM, ANN, GNN)
- NLP(Language models)
- Personalised recommendations(graph neural networks)
- Model evaluation and dashboard implementation
- Keras, Tensorflow, Pytorch
- LLM (LLama,Falcon open source models))
- Image processing
- Statistical analysis and inference
- Python3, Django, Docker, pyspark
- Team management
- Manage multiple projects
Accomplishments
Machine Learning: statistical models , feature selection using correlation and data normalization, transforming data, hyper parameter tuning, deciding loss functions and optimizers, ensemble models , bagging and Gradient boosting methods,PCA(principle component analysis)
Deep Learning: CNN , activation function, different layers, , regularization techniques, data preparation, data preprocessing, training models and
NLP: NER(named entity recognition), sentiment analysis, word2vec,CBOW,SKIPGRAM,Glove, BERT, TFIDF, N-gram,Transformers, Fast text embedding(char embedding).
Validation Techniques : AUC (Area under curve analysis) / ROC ( receiver operating characteristic curve),confusion matrix, Precision, Recall, F1 score.
Project : personalized recommendations to the user based on user history and demographics, using Graph neural networks (deep graph library).
Project : detecting products,shelves and positions in Retail store, using deep neural network
Project: Extracting invoice parameters , invoice number, date,account number,vendor,ship,and remit addressed
Project: extract contact entities , person name, title and company name email address from email threads and populate these details into sales force contact management screen
Project: Build, person ,facemask detection and social distance monitoring Video analytics application and deployed in SHINOBI CCTV monitoring app, Live Detection and streaming
Project : Text classification , intention detection in email threads, is email contains complaint, feedback, query, compliment, information.
Project : user activity monitoring tool , deep neural network to monitor user system , how much time spent on which application, browser , command line, media player, excell
Project : text classification, monitor user screen and classify the amount of improper text present on screen , to measure how much a child is exposed to abuse,hatred on social media platforms
Certification
Neural Networks And Deep Learning: coursera.org/verify/SLTJ3EGKFWQQ
Contact
Phase II, Amrita Nagar, Choodasandra, Bengaluru, Karnataka 560035
Timeline
Senior Data Scientist Level 3
Morgan Stanley
04.2024 - Current
Neural Networks And Deep Learning: coursera.org/verify/SLTJ3EGKFWQQ
04-2023
Senior Data Scientist Level 2
Condenast India
09.2021 - 02.2024
Data Scientist
IOPEX TECHNOLOGIES
03.2019 - 09.2021
Software Engineer
Tata Consultancy Services
06.2016 - 03.2019
BE - Electrical And Electronics
SASTRA UNIVERSITY
06.2012 - 06.2016
High School Diploma -
Vignan Junior College
06.2010 - 06.2012
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