Bread Financial Recruitment 2024 for Analyst-Data Science | B.E/B.Tech/B.Sc | 4 LPA*
Bread Financial Recruitment 2024– is scheduled to hire Analyst, Data Science for B.E/B.Tech/B.Sc graduates. The detailed eligibility and application process are given below.
Eligibility Criteria | ||
---|---|---|
Job Role | Analyst-Data Science | |
Qualification | B.E/B.Tech/B.Sc | |
Experience | 0-1 Years | |
Location | Bangalore | |
Salary | 4 LPA* | |
Detailed Eligibility Criteria For Bread Financial Off Campus Drive :
- Degree Required: Bachelor’s Degree
- Area of Study: Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science, or another quantitative field
- Years of Work Experience Required: Fresher or less than 1 year experience.
- Type/focus of work experience required: Must have done a Data science and Machine learning course.
Knowledge, Skills and Abilities:
Must:
- Data Science
- Machine Learning
- Structured Query Language (SQL)
- Python
- Strong Communication skills
Good to Have:
- Natural Language Processing (NLP)
- Cloud Experience (AZURE/AWS)
Essential Job Functions:
- Extracts and samples data, conducts data integrity checks and applicable data pre-processing such as treatment of missing values and outliers
- Conducts exploratory data analysis for preliminary data insights to drive the selection of modeling approach that best addresses the business problem,
- Reveals hidden data patterns by data mining using unsupervised learning techniques such as clustering analysis and factor analysis,
- Conducts feature engineering to create/derive model predictors with strong predictive power,
- Trains/tunes classification/regression models by applying supervised learning techniques such as generalized linear models assuming applicable underlying distributions such as logit and gamma, tree-based models such as decision trees, random forest, boosted trees, etc., and neural net models,
- Conducts proper model test/validation, and diagnoses and fixes model issues (e.g., over-fitting) when applicable. Sizes the impact of using the models in production as part of the current strategy. Presents results and business case to manager. Provides support for implementation and monitoring of solutions that are implemented.