Amina Kaltayeva

• Full-stack scoring model development. Provided comprehensive analysis solutions to build scoring, PD, LGD, EAD models using data from internal and external sources and applied advanced analytical methods to assess factors impacting creditworthiness of SME clients. Applied logistic regression/ tree-based models/ NN methods.
• Growth analytics. Built customer journey map to evaluate conversion rate at each step from loan request to loan issue. That exercise highlighted the need to introduce client pre-scoring (that is, target potential clients before they apply).
  
• Developed monitoring dashboard to track ML models' performance, stability of population and key product metrics: dashboard included factual information about product performance and dynamic forecast of achievement year-end targets. 
• Built early warning system development. Worked on Natural Language Processing with NLTK module of python for application development for automated monitoring possible increase in credit risk.
  

• Employed advanced knowledge of risk management and data science to teach challenging high-level courses (Microeconomics and Quantitative finance) to undergraduate students. Courses included econometrics and time-series models.
• Increased final exam passing rate by about 20%.
• Delivered undergraduate courses via classroom, online and hybrid methodologies to satisfy course curricula and meet student needs.

Main projects and responsibilities:

• End-to-end analytics system and implementation of unit economics. For large retail company re-built managerial reporting by introducing unit economics. That allowed developed the end-to-end analytics, prioritized expenses and cut next-year budget by 11%.
• Customer segmentation model. For large retail bank created segmentation model in Python to identify client profiles and marketing channels with highest CAC. Model is also used for additional product recommendations and new clients classifications. 
• Business processes re-engineering. For different companies reviewed business processes, created user-stories, identifying areas that required improvement and conducted process re-engineering. Processes included IT, procurement, sales, HR, budgeting. Applied data visualization and gap analysis.
• Quantitative risk assessment framework. For telecom company developed quantitative risk assessment model that helped to formulated knowledgeable forecasts for business and industry based on available financial information. Applied simulation techniques.
• Conducted seminars to teach clients how to assess and control risks at front line.
• Orchestrated multiple projects within strict timeframes and budget constraints by solving complex problems and working closely with senior leaders. Coached, developed and motivated team members, providing coaching and mentoring to junior colleagues.

- Managed of short-/long-run demand planning for two countries out of CEAB unit (contained 13 countries);
- Conducted post-launch reviews of marketing activities on impact on sales; 
- Was responsible for sales-out data management
Key achievements: (1) delivered a short/long-term demand forecast statistical model that allowed to rise forecast accuracy from 80% to 85; (2) designed and implemented an inputs collection worksheet that optimized period-close cooperation of several departments and saved around 4 working hours per period, (3) created a system of products’ unique codes in order to collect sales out data for further analysis