Data Scientist - Credit Risk Domain - BFS

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.