What We Do > Data Analytics > Advanced Analytics Consulting Services

Advanced Analytics Consulting Services

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

Blogs | Unlocking The Potential of Generative AI to Enhance Customer Experiences

Employing Advanced Analytics Consulting Services to Build Intelligent Applications

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

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Advanced Analytics Consulting Services

What We Offer

  • Classification and regression models using explainable and implementable advanced ML models like XgBoost, LightGBM, and decision trees  
  • NLP tasks such as text classification (multi-label), translation, and topic modeling  
  • Training state-of-the-art models (BERT-based models, such as Distil Bert and Roberta, and GPT-based models, like Latent Dirichlet Allocation) on cloud/on-premises environments, utilizing libraries such as NLTK, Gensim, Spacy, and TensorFlow  
  • 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 past data and profiling them into micro-segments to run promotional campaigns accurately to improve customer retention
  • Computer vision tasks like image classification, object detection, and object tracking  
  • Training state-of-the-art models (YOLOv5, resnet50, VGG-16, and SORT) utilizing OpenCV, PyTorch, Keras, and TensorFlow
  • Model deployment on edge devices/cloud/on-premises servers, which involve environment setup, containerization, latency testing, multiprocessing, and model optimization  
  • Model lifecycle management involves experiments tracking, monitoring (KPI drifts), and managing API endpoints on cloud/on-premises environments using MLOps tools (MLFlow, TensorFlow serve, and Kubernetes) 
  • Performing clustering analysis using density-based clustering and hierarchical clustering, 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 different surveys using hierarchical Bayesian models to determine individual and group utilities of the options
  • We develop credit lifecycle models (application behavior and collection) using explainable and robust ML 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 lifecycles and geographies 
  • We help reduce model development and deployment lifecycle to 8–12 weeks


Capitalizing on our Expertise

Our predictive analytics solutions have enabled our clients to proactively make the right decisions and improve their profitability and market shares.

Driving Business Objectives

Leverage data science solutions to enhance our customer experience, enabling us to deliver the best business outcomes.

Who We Work With


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