Credit Risk Data Scientist RESPONSIBILITIES: - You will be a key member of the Credit & Risk team at Zolve. The incumbent will be reporting into the Head of Credit & Risk at Zolve. - The role requires working with large data sets using quantitative techniques and building complex statistical models that learn from big data. Data sets will include traditional transactional data, customer attributes obtained at the time of onboarding and alternate data sourced from non-traditional data vendors. - Building propensity models for underwriting, collections, Cross sell, loss projections, budgeting etc. - Taking care of end-to-end delivery in predictive modelling, such as Data visualization, Data quality check -Cleaning, Aggregation, Data Segmentation - Working on cohort identification, development and validation - Working on Risk Based Pricing and Implementation - Understanding product and business offerings and give data driven insights to build risk strategies, acquisition strategies, product strategies, and overall business & market dynamics for portfolio growth. - Support day to day operational risk management and credit life cycle management. - We have a highly collaborative process and you are required to work across multiple teams and functions for developing cutting edge, creative and advanced analytic solutions and processes. REQUIREMENTS: - Candidate with 5+ years of analytical experience in applying statistical solutions to business problems - Bachelors or Post Graduate degree (Masters or Ph.D.) in Quantitative field such as Statistics, Mathematics or equivalent experience preferred - Required hands on experience with data analytics/programming tools such as Python and SQL is mandatory. Salford SPM/Hadoop/R/Hive are good to have. - Proficiency in some of the following statistical techniques: Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Neural Networks, Clustering, Principal Component Analysis, Factor analysis etc - Experience in predictive data Modelling using ML Techniques, ability to interpret complex and large data sets - Experience in banking / fintech / consumer lending industry preferred - Experience in risk analytics (model development, strategy and framework, scorecard development, documentation, validation, governance, implementation and automation etc.) will be a strong advantage - Understanding of credit bureaus and non-traditional data providers will be a plus - Demonstrated ability to innovate solutions to solve business problems - Results oriented with strong analytical and problem solving skills, with demonstrated intellectual and analytical rigor - Good business acumen with strong ability to solve business problems through data driven quantitative methodologies - Detailed oriented, is expected to ensure highest level of quality/rigor in reports & data analysis - Proven skills in translating analytics output to actionable recommendations, and delivery The role is based out of Bangalore.

Bangalore

Zolve - Data Scientist - Credit Risk Domain 

Job Description for Zolve - Data Scientist - Credit Risk Domain  in ZOLVE INNOVATIONS PRIVATE LIMITED in  Bangalore for (5-12) years of experience. Apply Now!