Job Opportunity for Data Science and Data Analytics Lead at Niti Ayog

1. Name of position

Data Science and Data Analytics Lead (Consultant Grade I)

2. Number of positions

1 (One)

3. Method of recruitment

Contract Based through Open Market

4. Age Limit

Candidates should be below 45 years of age as on the date of advertisement

5. Tenure

The engagement would be purely on contractual basis for a fixed period of two years which may be extended by one year at a time up to a maximum tenure of five years i.e., 2+1+1+1 years from the date the candidate joins the assignment. However, being a contractual arrangement, the engagement could be terminated at any time by the competent authority without assigning any reasons.

6. Remuneration (per month)

Rs. .80 Lakh to Rs. 1.45 Lakh (Consolidated inclusive of all)

7. Education qualification

Essential

Master’s Degree or equivalent in Computer Science/Engineering/Technology /Economics/Statistics/Operation Research/Public Policy/ Development Studies/ Business Administration/Management; or BE/B.Tech or MBBS or CA or ICWA or possessing any Professional Degree in related fields earned after study of 4 years or more acquired after 10+2

Desirable

Persons with M.Tech., M.S., Ph.D, additional qualifications, research experience in areas such as Information Systems Architecture, Design & Development of Enterprise Business Solutions, Data Engineering, Data Science with specialisation in computer vision, Neural Networks, Visualisation tools (Tableau & Power BI) experience, published papers and post qualification experience in the relevant field would be preferred.

8. Experience Essential

Overall 3-8 years of work experience with minimum 2 years of experience in programme monitoring, evaluation, research or related fields. Multi-sectoral experience (combination of national/international public, private and civil society sector) preferred.

• Relevant research experience at appropriate level backed by suitable publication records.

Preference will be accorded to candidates with

Candidates with experience in statistics, machine learning, data wrangling, data visualization tools, application of cutting-edge technologies in surveys, data analytics, rigorous econometric analysis of large datasets are encouraged