What We Do > Data Analytics > Advanced Analytics Services

Advanced Analytics Services

At SGA, we are focused on providing advanced analytics solutions where we take our analytical partnership to the next level.

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Using our advanced analytics services, we combine data assets & ML models to build intelligent AI applications for the future.

At SGA, our analytics team enhances the data operations team's skills with data science and machine learning experts who are well versed in big data and machine learning tools and frameworks such as Python, R, TensorFlow, Keras, Pytorch, Databricks, Spark, Azure Machine Learning, and Amazon Sagemaker, amongst others. Using our advanced analytics services, we build OCR and NLP-based machine learning pipelines to help extract valuable insights from unstructured data across core data sources, including financial data, reports, earnings summaries, and social media.  

Our advanced analytics solutions help us in maximizing our client's ability to make data-driven decisions by building advanced machine learning models using relevant data in different contexts as per our clients' domains - BFSI, Media and Entertainment, Technology, and Manufacturing.  

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What We Offer

  • Classification and regression models using explainable and implementable advanced ML models like XgBoost, LightGBM, decision trees, etc.  
  • NLP tasks such as text classification (multi-label), translation, topic modelling, etc.   
  • Training state-of-the-art models (BERT-based models such as Distil Bert, Roberta, etc., GPT-based models, Latent Dirichlet Allocation) on cloud/on-premises environments utilizing libraries such as NLTK, Gensim, Spacy, TensorFlow, etc.  
  • Recommendation systems involving content-based filtering, collaborative filtering, and hybrid algorithms  
  • Time series analysis and forecasting using ARIMA, LSTM, TFT, DeepAR, and other suitable techniques  
  • Making use of Churn Attrition models to identify the risk of attrition accurately based on the past data and profiling them into micro-segments to run promotion campaigns accurately to improve customer retention
  • Computer vision tasks like image classification, object detection, object tracking, etc.   
  • Training state-of-the-art models (YOLOv5, resnet50, vgg-16, SORT) utilizing OpenCV, PyTorch, Keras, TensorFlow etc.
  • Model deployment on edge devices/cloud/on-premise servers, which involve environment setup, containerization, latency testing, multiprocessing, model optimization, etc.  
  • Model lifecycle management involves experiments tracking, monitoring (KPI drifts), and managing API endpoints on cloud/on-premise environments using MLOps tools (MLFlow, TensorFlow serve, Kubernetes, etc.) 
  • Performing clustering analysis using density-based clustering, hierarchical clustering, etc., with appropriate distance measures 
  • Network analysis with Markov chains and BFS/A* search techniques 
  • Market survey designing using fractional factorial design and analyzing results of choice-based conjoint/ max diff surveys using hierarchical Bayesian models to determine individual and group utilities of the options
  • We develop credit lifecycle models (application behavior & collection) using explainable and robust machine learning algorithms like XgBoost and LightGBM  
  • We create intelligent features using Bureau and other alternative data sources. We bring decades of credit risk management expertise across product life cycles and geographies 
  •  We help reduce model development and deployment life cycle to 8-12 weeks


Capitalizing on our Expertise

Our predictive analytics solutions have enabled our clients to proactively make the right decisions & improve profitability & market share.

Driving Business Objectives

Leverage data science solutions to enhance customer experience enabling us to deliver business outcomes.

Who We Work With


media and entertainment services

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