Data Scientist - Credit Risk
Job role :
- Develop and plan analytic projects through understanding the business objectives in the team strategy roadmap
- Develop robust analysis and deliverable plans to support clear and shared understanding of project requirements and goals
- Design and develop analyses based on business requirement needs and challenges.
- Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, hyperparameter tuning, ensembling etc.
- Design and implement Machine learning / Deep learning predictive models/NLP utilizing diverse sources of data to predict user behavior.
- Utilize analytical applications Python /NLP to identify trends and relationships between different pieces of data, draw appropriate conclusions and translate analytical findings
- Development of Models using Machine Learning/ AI/ Text mining models
- Develop data-driven decisions and insights to support organisation and its partners credit business, monitor the performance of the credit products, and adjust priorities according to the dynamic world operate in.
- Analyze large volumes of internal and external data using common data science tools(Python, SQL/NoSQL etc.) to deliver unique insights into relationships across a wide array of products, platforms, customers and experiences.
- Develop connections between business problems throughout the Credit Risk domain and deliver analytic solutions to meet the most pressing demands
- Communicate complicated analytic results in brief, concise formats tailored to a variety of audiences
- Document, improve, and automate existing Credit reporting processes to reduce the burden of internal and external reporting requirements on all members of the Credit team
- Manage and improve the process of data collection, ingestion, manipulation, and display for risk related reporting processes.
- Collaborate with all aspects of the Credit business including a broad range of partners to plan and deliver fully developed solutions for Asset Quality monitoring and reporting
- Lead the planning, development, and delivery of analytic and reporting projects from start to finish
- 2 to 6 year experience in advanced analytics, model building, statistical modelling,
- Solid technical / data-mining skills and ability to work with large volumes of data; extract and manipulate large datasets using common tools such as Python and SQL other programming/scripting languages to translate data into business decisions/results
- Be data-driven and outcome-focused
- Must have good business judgment with demonstrated ability to think creatively and strategically
- Must be an intuitive, organized analytical thinker, with the ability to perform detailed analysis
- Takes personal ownership; Self-starter; Ability to drive projects with minimal guidance and focus on high impact work
- Looks for opportunities to build owns skills, knowledge and expertise.
- Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)
- Experience in risk and credit score domains preferred
- Comfortable with ambiguity and frequent context-switching in a fast-paced environment.
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