As businesses, governments and communities become more data driven in their decision making and business operations, demand on the new and innovative AI and Analytics related capabilities are exponentially growing. As a data scientists build compelling value proposition for flexible and futuristic Analytics driven insights and solutions. You will partner with sector teams, global markets team to sense, originate, qualify opportunities, and pursue the deals to closure.

Responsibilities:

• Originate new Analytics AI opportunities
• AI controller design, development, and implementation for industrial applications
• Own end to end delivery of, a) large complex Analytics AI led transformation programs, b) small and nimble business insights initiatives to realize quick gains, c) work with tk and Partners to bring the best tools and delivery methods.
• Own the offerings and assets on key components of Analytics AI value chain, including understanding burning platform and industry trends, define and frame hypothesis,
• Build key partnerships with top tools, platform and fintech.
• Improvise new and innovative data assets and drive its adoption to the market.
• Be a thought leader on AI
• Should have hired and nurtured talent and grow them in market facing specialists and consultants. Should have built a community of practice on data.
• Formulating, suggesting, and managing data-driven projects which are geared at furthering the businesss interests.
• Collating and cleaning data from various entities
• Selecting and employing advanced statistical procedures to obtain actionable insights.
• Cross-validating models to ensure their generalizability.
• Producing and disseminating non-technical reports that detail the successes and limitations of each project.
• Suggesting ways in which insights obtained might be used to inform business strategies.
• Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.

Experience :

Required Technical and Professional Expertise

• Someone who has traversed the Analytics AI value chain, having moved the clients from data to insights.
• Deep expertise in applying Analytics for two or more industries (cement, sugar, steel, mining, automotive, aerospace, Manufacturing, Oil Gas etc.)
• In depth understanding of AI tools across Machine Learning, Intelligent Automation, Conversation Intelligence and how they all come together to build AI ecosystem
• Worked in a third-party consulting, service, technology organization for a fair share of the career.
• Consulted clients on aspiration to make them information led decision making business.
• Hands on expertise in developing and implementing predictive models (statistical and machine learning) for large enterprises.
• Proven ability to enhance value of an opportunity through new technology
• Ability to run multiple and disparate client conversations, opportunity pursuits, and handle the execution of dynamic practice agenda.
• Advanced degree in any engineering discipline
• Extensive experience as a Data Scientist.
• Proficiency in R or Python, where the former is preferred.
• Hands-on with supervised, unsupervised, deep learning, visualization, NLP methods techniques
• Hands-on with application of data science to industrial applications [cement, sugar, steel, mining, automotive, aerospace etc.]
• In-depth understanding of SQL.
• Competent in machine learning principles and techniques.
• Demonstrable history of devising and overseeing data-centered projects.
• Ability to relay insights in laymans terms, such that these can be used to inform business decisions.
• Capacity to foster a healthy, stimulating work environment that frequently harnesses teamwork.
• Compliance with prevailing ethical standards.

Preferred Technical and Professional Expertise

• Support both the development of new business opportunities and the delivery of analytics platform services to clients.
• Advise clients in the planning, design, management, execution, and reporting of the core components for big data offerings. Skills include architecture, tool selection, data lake design and implementation
• Strong relations in the Indian market with key client decision makers