Experience :
- 1-3 years of experience in using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience working with data mining, and creating data architectures
- Knowledge of a variety of machine learning techniques (clustering, decision tree, random forests, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.
- Exposure and experience in data visualization skills on R, Tableau, Power BI to build dashboards
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques in the field of research and analytics.
Essential Skills:
- Should have strong data analytics skills, should be proficient in statistical analysis software: preferably R, knowledge of data visualization software (Tableau/Power BI), should have experience in predictive modeling and machine learning (should have supervised and unsupervised techniques like regression, decision tree, random forest, clustering).
- Should have knowledge about dashboards and credit scoring tools.
Qualification
- Degree in B.Tech/BA/BCom/MBA from a reputed university,
- Other relevant professional qualifications in line with areas of specialization.
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