Key Responsibilities :
- Using data science in various facets of SME lending, including (but not restricted to) credit scorecards & portfolio monitoring frameworks, business insights, campaign management, propensity, and pricing
- Data mining or extracting usable data from valuable data sources
- Using machine learning tools to select features, create and optimize classifiers
- Carrying out pre processing of structured and unstructured data
- Enhancing data collection procedures to include all relevant information for developing analytic systems
- Processing, cleansing, and validating the integrity of data to be used for analysis
- Analysing large amounts of information to find patterns and solutions
- Developing prediction systems and machine learning algorithms
- Presenting results in a clear manner
- Propose solutions and strategies to tackle business challenges
- Collaborate with Business and IT teams
Skills required
- Should have knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable
- Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies
- Proficiency in handling imperfections in data
- Hands-on experience with data science tools
- Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Tableau that help to visually encode data
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