Risk Consultant - Statistical Modelling/ Business Analysis - Financial Domain
- Responsible for Development of model & Strategies to solve the business problem in Financial domain.
- Provide consultancy to client to change their business process.
- Individually mange Client communication/Customer engagement
- Understand business requirements to translate business problems into analytics problems and construct analysis road-map based on the business context
- Responsible for creation of test plan according to requirement of the model- verify, validate and execute the entire plan
- Expertise in conceptualizing business problem into a tangible deliverable (an exhaustive report), model documentation and validation report writing, following regulatory guidelines.
- Manage large volumes of structured and unstructured data, extract & clean data to make it amenable for analysis
- Analyse big data using statistics, econometrics, mathematics, operations research, and text mining techniques
- Develop good visualization to communicate business insights from analysis and make actionable recommendations
- Help deploy analytics solutions and enable tracking of business outcomes to measure return on investment
- Keep up with cutting edge analytics techniques and tools in the continuously evolving area of decision science
- Assist in developing/coaching individuals technically as well as soft skills during the project.
Required Candidate profile
- 2+ years of work in statistical modelling and business analysis role
- Exposure in developing / Validating Credit risk models.
- Developed some models/ strategies to solve a business problem especially in credit risk/Marketing domain for financial products.
- Have worked for at least 2 products in financial domain for 2+ years.
- Bachelors/ Masters in Economics, Engineering, Mathematics, IT, Statistics and MBA/PGDBM
- Well versed with various statistical analysis methods such as Regression, Logistic regression, decision trees, other segmentation methods
- Strong skills of SQL to extract and build data for various statistical analytics
- Strong Analytical skills
- Hands on experience in statistical modelling software such as SAS or R
- Strong Microsoft Excel, Access and PowerPoint skills.