Data Science Head

Role & Responsibilities :

- The Primary focus of this role is to develop and manage applications involved with Search Systems.

- Maintain and upgrade search indices for large document repositories, as well as optimizing indexing/queries and supporting analytics.

- He will be leading a Team of search engineers who build Tags, taxonomy, Thesaurus and ontology data models and standard to define and organize our customers search experience.

- Drive and coordinate cross-functional projects with broad range of Loan, Insurance and investment products owners, engineers, designers and other groups that may include architecting new data solutions

- Analyze website metrics and customer behaviour data to make intelligent decisions on optimizing our search model.

- Collaborate and consult directly with key stakeholders, technical teams and leadership on solutions for taxonomy and metadata that will positively impact the customers search experience

- Expand and refine data retrieval techniques to use our extensive product catalog and improve customer data quality

- This role is for machine learning and data-oriented product development (horizontal capability builds) but it will also require strong program management and execution skills.

- Technical Interactions with vendor or partners in technical capacity for business/capability deliverables.

- Develops proof of concept to prove or disprove validity of concept. Work with cross functional team to integrate these models into larger solutions.

- Works collaboratively in a multi-disciplinary team environment.

- Establishes and maintains professional networks with subject matter experts.

- Responsible for artificial intelligence / machine learning technology and application analysis, understand latest industrial and academic developments in AI/ML.

- Design competitive AI/ML services and user experience for next generation products and create prototypes for demonstration.

- Strong empowerment and self-drive is a must.

Ideal Candidate :

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

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

- Strong IT & Business interactions capability

- Strong team player with exceptional program management.