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Data Science Services


More data doesn’t help. Smart insights do.


It is difficult to extract relevant information from the heaps of data you have collected. We help you to dissect, streamline and analyze your data to derive meaningful information that enables making better business decisions.

We bring state-of-the-art practices, processes, and tools to help you at any stage of your analytics. We dig deep into your data and mine information that is significant, accessible and workable. We help you innovate faster and increase your efficiency.


Predictive Modelling

To realize the full potential of machine learning and data science investments, it is important to align the investments and initiatives with existing business processes. We operate at the intersection of software development, data science, and deep industry expertise

We work with our clients for identifying use cases and developing machine learning solutions to solve tangible business problems. 

Our sample machine learning projects :

  • Machine Learning Engine for Natural Language processing for identification of events, entities for pharmacovigilance reporting
  • Serious Adverse Event Classification model to predict serious adverse events based on unstructured natural language text


Visual analytics

Our consultants bring extensive experience across industries in creating dashboards and interactive visualizations to support business decision making. Traditional static reports used in the industry require detailed manual work for traceability, interpretation, and analysis. Interactive visualizations and dashboards can enable pharmaceutical companies to get a high-level understanding of statistical metrics, as well as get detailed traceability behind the metrics at click of a button. 

We support dashboard through the following technical options:

  • Program Languages Driven: such as Shiny R, Python, or native JavaScript
  • Dashboard Products: such as Power BI, Tableau, Qlik, Tibco Spotfire 
  • Hybrid: Integrating ETL/Data analysis in SAS, SQL, R, Python with visualization tools to create production-ready visualization products


Data Engineering and Management

There is a great need and opportunity in the pharmaceutical industry to acquire, and analyze vast amounts of complex, and disparate data. We provide technical capabilities across data management, data engineering, and governance to create products to ingest, analyze, and make sense of large disparate datasets.

Sample projects we worked on:

  • Data Lakes using on-premise (Hadoop), and cloud-native technologies (such as AWS S3)
  • Batch and stream data pipelines using technologies such as Hadoop, Spark, and Apache Kafka