Roles and Responsibilities

Your primary job responsibility will include (and not be limited to):

• Owning new initiatives for learning content and experience for our flagship program DSBA

(Data Science & Business Analytics)

i. Ensuring ongoing review of the learning content and identifying opportunities

to improve quality in terms of appropriateness, accuracy, richness.

ii. Ensuring the efforts towards updating the content as well as creating additional

content - videos, reading material, exercises and assignments.

iii. Drive cross-pollination of ideas and knowledge with in-house data science and

academic operations team to deliver in-house solutions and translate them

into learning material & case studies for learners

• Leading initiatives as an in-house data science expert to deliver solutions to key

business problems across operations and customer experience.

i. Improve and evolve business intelligence layer for operation func

tions to enable

automated delivery of insights to aid decision making on a regular basis (daily,

weekly, monthly)

ii. Develop advanced analytics systems using driver and/or predictive models to

identify factors that influence business outcomes like learners' success, and

help design and automate interventions to accelerate growth

iii. Use insights derived from ad-hoc data analysis to answer ad-hoc questions

as well as drive processes improvements so that Great Learnings business

requirements are met

iv. Refine existing solutions & products as well as handcraft new features in the

Learning Management System for superior end user experience

• Create unique learning experiences that enable Great Learning customers to have a delightful
•  

learning experience and meaningful outcomes.

i. Conceptualize, plan and execute hackathons & ad-hoc competitions.

i. Fostering and leveraging relationships with industry leaders in Analytics to

organize conferences, panel discussions, Analytics industry sessions

Desired Candidate Profile

• Solid understanding and working knowledge of advanced techniques like supervised &

unsupervised learning, including but not limited to, hypothesis testing, regression, clustering,

decision trees, prediction techniques, model tuning and model performance measures etc.

• Good aptitude, ability to think logically and problem-solve
• Ability to work under pressure and tight deadlines
• Ability to learn quick - ability to learn business, processes, techniques and technologies on the go
• Potential ability to lead teams
• Good understanding of what analytics is - from data to decisions
• Good ability to work with complex, unstructured data from multiple sources - consolidate,

analyze, interpret, clean and transform to get it ready for analysis

• Ability to design approaches to solve a problem using data analysis techniques
• Ability to interpret data, present/visualize metrics and extract meaningful insights to

answer business problems

• Strong working knowledge of R/Python, Excel
• Excellent oral and written communication skills