Data Science Practice Manager

Profile Requirements

Suitable candidates would meet 5 or more of the following requirements:

1. Worked on at least two large big-data projects and/or data-driven decision making projects involving data engineering, analytics and data science. (mandatory)
2. Possess expertise in the tools and techniques involving data preparation, movement and analysis of data – including visualization, machine learning and NLP. (mandatory)
3. Demonstrable experience and expertise in the selection and evaluation of ML algorithms to suit specific problems. (mandatory)
4. Fair understanding of at least one of the following verticals – by virtue of solving data science problems in that domain: Insurance, Manufacturing, and Education.
5. Performed in the role of a data science / analytics team leader – managing technically strong people, building capability and executing projects.
6. Familiar with recent developments in Analytics, ML Operations, automated machine learning and conversational AI.
7. A master’s degree in Mathematics, Statistics, Machine Learning, Big Data Analytics, Computer Sciences or equivalent.
8. Possess excellent verbal and written English communication skills as necessary for a leader. (mandatory)
9. Possess excellent interpersonal and people skills. Able to work with a predominantly remote workforce. (mandatory)

Job Description

Selected candidate would:

• Build and lead a strong team capable of delivering challenging data analytics and data science projects.
• Head the delivery of analytics and data science projects for the organization – achieving project success and customer success objectives. Put in place, the necessary technical, management and governance processes to execute such projects successfully.
• Understand regulatory compliance issues arising out of handling large volumes of potentially sensitive data – both for customers as well as for the company; and address these requirements through adequate processes and solutions.
• Get to know the strengths and weaknesses of each of the team members and help them meet their career aspirations by coaching them 1-on-1 and providing them with the necessary resources.
• Collaborate with Sales & Pre-sales teams – interacting with prospects and customers, understanding their needs and formulating solutions for their analytics and data science needs. Develop the core technical content for proposals, presentations, statements of work (SOWs) for use by the sales/pre-sales teams.
• Provide the necessary technical guidance to projects involving the practice specializations and tools.
• Work with the executive leadership team in actively contributing towards the company’s strategic goals and aligning with the company values.