• Sole full-stack developer, responsible for the architecture and development of a scalable Python/Django backend, monolithic application, including building custom CRM, warehouse logistics modules and e-commerce app to support over 100,000 monthly users • Designed and implemented front-end features using HTML, CSS, JavaScript, and Bootstrap, ensuring consistent and seamless user experience across multiple devices and screen sizes • Evaluated and selected PostgreSQL, Redis, and Elasticsearch to design a scalable and robust architecture. These technologies were chosen to ensure efficient data storage, caching, and search functionalities to meet growing user demands • Implemented asynchronous task processing using Celery and RabbitMQ to handle background jobs, which improved system performance and ensured more responsive user-facing operations • Improved site structure and optimized page load times by refining the layout and enhancing caching mechanisms and content management practices, resulting in smoother navigation and enhanced user experience • Collaborate with management, sales, and marketing teams to gather requirements and translate business needs into technical solutions, including CRM automation and workflow optimizations, to support business goals • Led the full development life cycle from concept to deployment and support, overseeing both back-end and front-end development. Utilized Agile practices and Git workflows to ensure smooth development and version control processes

Projects: ▪ Age Prediction from User Photos. Built an age estimation model for targeted marketing and product control, achieving a mean absolute error of ~6 years.▪ Customer Churn Prediction. Created a predictive model to identify at-risk customers, enhancing retention strategies and customer satisfaction. ▪ Comments Sentiment Analysis. Developed an NLP model to detect toxic comments with an F1-score of 0.768, improving content moderation on an e-commerce platform. ▪ Hourly Taxi Order Forecasting. Built a time series forecasting model (RMSE 15.97) using XGBoost, LightGBM, and ARIMA to optimize driver allocation for peak hours. ▪ Optimization of Manufacturing Costs in a Metallurgical Plant. Achieved 3.83% accuracy improvement in steel temperature prediction, enhancing cost efficiency for a metallurgical plant.

- Managed sales of personal protective equipment to three key clients in mining, metallurgy, and construction industries- Collaborated with engineers in Europe and the US to develop technical solutionsDeveloped a local architecture for the SalesForce CRM, including CRM workflow, report formats, and user playbooks- Created two programs for SFDC training and testing using Python, Tkinter, Pandas, and PIL- Created a project management system for Rent-a-Rep, including a database for employee management using Excel, and a sales and ROI monitoring system using Python, Pandas, Matplotlib, Seaborn, and PowerBI

- Managed sales and achieved growth and revenue targets- Reported directly to BDM in European office - Developed and implemented strategic plans for sales growth- Trained sales team on new products and sales techniques- Collaborated with engineering team to develop new products