- PhD/MTech/BE/ BTech/MSc in CS or Math, Operation research, Statistics, Econometrics or in any quantitative field

- 6+ years of industrial experience in Search, Information retrieval, NLP, Machine learning, predictive analytics solution development and deployment

- Strong Problem-solving ability

- Should have strong experience in anyone or more programming languages Python or JAVA. Experience in RESTful, Web Services,

- Experience in using Python, R, SAS or any other statistical software (plus other open source libraries)

- Skills with Shell/Perl (or similar scripting language), Scala and Java

- Experience with development tools like Eclipse, Git, Gradle, Jenkins, Jira, JFrog Artifactory etc.

- Experience with web application server like Tomcat, Jetty, JBoss etc.

- Strong understanding of OOP design patterns and industry best practices.

- Fair knowledge of scripting and working in Linux environment

- Good to have Experience of building Solutions with latest front-end technologies (JavaScript libraries like React or Angular, CSS3, HTML5).

- Hands-on experience of API Integration single-sign -on and token-based authentication. Experience integrating with SQL and NoSQL databases (Cosmos DB, Cassandra, MongoDB)

- Good understanding of DevOps pipeline like Azure Devops. Experience in Agile environment

- Experience in any of the following area could be plus : Lucene based search engines (Elasticsearch, Solr)

- Experience Container Orchestration technologies (Kubernetes), distributed systems, scalable data analytics technologies (Spark)

- Experience in mentoring junior team members, and guiding them on machine learning, NLP, Computer Vision, Speech analytics and data modeling applications

- Strong communication and data presentation skills

- Skills with Relational Databases, Data warehouses, Structured & Unstructured data forms.

- Publications /patents/presentation in recognized Machine Learning and Data Mining journals/conferences is preferred

- Solid knowledge in deep learning algorithms and AI system design and architecture.

- Strong hands-on nature (ability to self-code is a must).

- Strong capability to work on server class (cloud machines) for data science capability builds