RA with SRITNE

 

Job Description :

The Srini Raju Center for Information Technology and the Networked Economy (SRITNE) has an open position for a Senior Research Associate with research interests in technology, technological innovation, and the digital economy. Ideal for someone with strong data analysis skills, relevant experience in data sciences, excellent written communication skills, and looking for a steppingstone to a world-renowned PhD program.

Research staff from SRITNE can choose from multiple career trajectories after their stint at the centre. Researchers have typically secured admissions to leading doctoral programs worldwide, including PhD programs at various University of California campuses, INSEAD, London Business School, Carnegie Mellon University, Cornell University, NYU, University of Texas at Austin, University of Maryland, University of Toronto, Columbia University, and University of Minnesota. Alternatively, research staff has gone on to assume resume-oriented positions in the corporate sector as well.

RESPONSIBILITIES 

·         Own research projects in diverse areas such as technology innovation and entrepreneurship, business value of technology, effects of the digital economy and digital business models, and the impact of technology interventions on public policy

·         Drive various aspects of the research process, including literature review, data collection, data analytics, preparing presentations, and writing and formatting academic articles. There will be opportunities to independently develop research ideas and co-author papers with faculty.

·         Data collection, analytics, and report writing

QUALIFICATIONS  

1.     For Research Associates: Master’s Degree in Computer Science/ Statistics/ Mathematics/ Engineering/ Economics from a top tier college.

SKILLS AND INDUSTRY EXPERIENCE

1.     Five (5) years of prior work / research experience is mandatory; experience must be accompanied by knowledge of statistical programming packages like Stata, R, and Python

2.     Advanced machine learning (e.g., LASSO, random forest, gradient boosting, decision trees, etc.) skills will be seen as a huge advantage

3.     Extremely comfortable with collecting, cleaning, normalizing and manipulating large datasets (cross sectional and time series); skilled in exploratory data analyses, creative data visualization and infographics generation  

4.      Ability to convert technical papers into data briefs, policy briefs, op eds etc. is a plus

5.     Resourceful, detail oriented, excellent organization skills, and demonstrated ability to multi-task and meet deadlines

6.     Motivation to learn and strong work ethic are necessary

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Contact us at

040 23187777

0172 4591800

Timings

Monday- Friday, 08:00 to 18:00