MIS Executive - SQL & Excel Mandatory (Maharashtra)

Crest Premedia Solutions Pvt. Ltd - Date posted: 26 Jul 2019
Purpose of the role:- Build bespoke data pipelines for further data analysis and to merge with our internal database of literature and other content. Develop document deduplication/matching algorithms. Build volume prediction models for content acquisition processes Conduct feature engineering on acquired data to support machine learning projects, such as document classification Specific Requirements:- 1. Qualification:- Degree in Computer Science or Statistics or in life science with strong experience in data interpretation & analysis 2. 3-5 years experience with programming languages, preferably SQL and Python or R 3. Demonstrated ability to extract and analyze data from large data tables or XML 4. Experience with data/system integration via APIs 5. Experience with building, operating, and maintaining data processing pipelines 6. Familiarity with content acquisition, for example from literature search engines, RSS feeds, web crawling, etc. 7. Experience with Kafka, MongoDB a bonus 8. Experience in workflow-based applications 9. Blends domain knowledge, math and statistics expertise, and programming skills 10. Ability to collaborate effectively with different teams 11. Extraordinary degree of intellectual curiosity 12. Ability to quickly pivot based on unexpected results or management directive 13. Easily prioritize and set direction in a fast moving environment 14. Self-motivated Key Tasks:- 1. Build bespoke data pipelines for further analysis and to merge with internal database of literature and other content 2. Sources: XML, Excel, API 3. Titles, identifiers, and metadata 4. Merge with SQL Server tables 5. Summaries and visualizations of data 6. Develop document deduplication/matching algorithms 7. Literature articles typically: title, DOI, citation details 8. Implement algorithms within existing process or apply for ad-hoc processes 9. Build volume prediction models for content acquisition processes 10. Regression analyses 11. Use of external and internal databases 12. Conduct feature analysis and engineering on acquired data to: 13. Improve search precision and recall 14. Improve volume prediction models 15. Support machine learning projects, such as document classification 16. Any other tasks as required by management...

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