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Data Engineer - Health Tech startup

Kyvor Genomics , Chennai, Bangalore · · Full-time employment · Programming

Job Summary: 

The Data Scientist / Developer along with the IT team develops innovative heath analytics system based on machine learning approaches by integrating medical information and genomics data.

Job Responsibilities:

  • Big Data innovative health analytics. Provide health and biological insight based on machine learning approaches in integration of medical information, genomics and behavioural data.
  • Apply cloud compute based real time queries of structured and unstructured data. Speed and accuracy optimization.
  • Designing and developing algorithms of data analysis and visualization solutions.
  • High throughput data processing, mining and curation, including detailed analysis, standardization and mapping of longitudinal phenotyping data and ontologies.
  • Increase internal and external adoption of advanced data analytics solutions and dashboards.
  • Identify new research opportunities, and develop innovative technology solutions to address multi-dimensional research questions.
  • Familiarity with genomics technologies and analysis methods as well as facility with scripting or automated tools to prepare large data sets


  • Experienced and fluent with statistical programming language R, PRocessing.js, Python, and others for data extraction, analysis and visualization (mandatory)
  • Advance degree in data science, statistics, computer science or related fields.
  • Exposure to healthcare, genomics and bioinformatics domains and its data types are a plus
  • Text Analytics using NLP
  • Experience with at least one machine learning platform such as TensorFlow, Caffe, Theano, CUDA, MXNet.
  • Experience with the implementation of text mining algorithms on structure and unstructured data.
  • Database - NoSQL such as MongoDB, MySQL, PostgreSQL
  • Data curation and data integrity
  • Strong critical and computational/ analytical skills. Should be familiar with SQL and relational databases. Knowledge of additional databases, RDF, and Linked Data approaches would be a strong advantage.
  • Machine learning algorithms and neural networks.
  • Fluency in writing APIs
  • Solid foundation of data structures, standardization and algorithms development.
  • Strong communication and global collaborations skills.
  • Peer reviewed publications in the domain of data science and bioinformatics are a plus

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