Senior HR Recruiter at Skillventory
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Machine Learning Role - Data Science/Analytics (6-7 yrs)
What you'll need to bring to the party
- Artificial intelligence concept in lending segment and Model Development skills
- Business Development using different model techniques
- Solution Design
- Understanding of techniques and algorithms of artificial intelligence which may be used to address business issues.
- Understanding of the principles and applications of the relevant Business Lines analytics solutions range.
- Extensive experience across the credit lifecycle
- Good knowledge of relevant statistical packages (e.g. SAS, SQL, Python and/or R).
- Good knowledge of programming languages
- Knowledge of advance machine learning algorithm
- Strong communication skills, including proficiency in writing reports and presenting technical work
- Strong interpersonal skills
- Ability to train and upskill analysts within the team
What you'll be doing
- Help team in developing and deliver top quality analytical solutions and models that follow best practice procedures and processes.
- Ensure quality and accuracy of own work and the work of any Analysts/Modellers on the project
- Specify data extraction and manipulation routines for complex/non-standard projects, providing guidance to other Analysts/Modellers where necessary.
- Interpret ,supervise and train others in the interpretation of analysis results.
- Upskill team members to enhance their skillsets and improve the quality of their modelling and solutions
- Ensure that all critical business issues are identified through data analysis and AI
- Implement appropriate quality control procedures for all modelling and analysis reporting.
- Reduce error rate & re-run frequency. Meet both the analytical, & business objectives.
- Produce the best quality models that can be produced within the given project timeline.
- Analyse and confirm the integrity of source data to be evaluated.
- Perform audits to support the implementation and accuracy of AI/ML models and other decision tools.
- Be organized, well-document the project by using set-up templates or versions thereof & meet project deadlines
- Collaborate with internal and external stakeholders to determine the appropriate performance measures and statistical metrics to be applied during the analysis project
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