Data Scientist

Skills: Statistics, Linear Algebra, Machine Learning, Natural Language Processing, Deep Learning, Computer Vision, Data Structure, R, Python, SQL.

Education: Bachelor s/ Master s/Ph.D. degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent field.

Experience: Overall experience of minimum 6-7 Years. Proven experience of 3-4 Years.

Roles & Responsibilities:

The role of the data scientist will be crucial in the analysis of intricate datasets to provide machine learning algorithms, predictive models, and insightful extracts. Working in cross-functional teams, you will apply data-driven methodologies to address business problems and offer practical suggestions.

1. Excellent skills in machine learning/deep learning-based algorithms with structured/ unstructured data; developing analytical insights and statistical models that optimize business.

2. Strong mathematical-statistical understanding behind the algorithms.

3. Proficient in Supervised ML, Unsupervised ML.

4. Industry experience in recommendation system, data science, and analysis.

5. Good in the evaluation of the performance of various data metrics.

6. Experience in conceptualizing and developing machine learning solutions in an ML engineer or data scientist, building, and deploying ML models, or hands-on experience developing deep learning models.

7. Experience in process knowledge and analysis, proficient at detecting patterns or problems that could affect overall data integrity/ solution.

8. Ability to think through alternatives, coming to decisions quickly, and following through with execution to resolve issues at the source.

9. Experience writing and speaking about technical concepts to business and giving data-driven presentations. Research data science industry trends.

10. Develop a compelling product vision.

11. Set the product roadmap that clearly outlines the future releases and longer-term product strategy.

12. Prioritize work for the data science, data engineering, and advanced analytics teams.

13. Manage and articulate a product backlog of ideas.

14. Must have working exposure in Agile methodology.