Alexander Polyakov Email & Phone Number

London Area, United Kingdom

❖ Created a CRM personalization framework using machine learning models for new product discovery and promotional offers. This initiative increased key metrics, such as Product Adoption and LTV, by over 8%❖ Developed an A/B testing platform and segmentation framework, including evaluation, pipelines, dashboards, streamlit app. This tool empowered over 40 product analysts in the company to design and evaluate their experiments, accelerating decision-making by a factor of three❖ Developed LLM services for evaluating customer reviews using RAG and conducting marketing geo-experiments. These services significantly improved the processing of user feedback and accelerated decision-making on key products by a factor of four❖ Facilitated cross-functional collaboration among Data Science, Product and Marketing teams to enhance operational efficiency and strengthen organisational cohesion. Managed junior team members and mentored two collaborative projects between Wise and LSE in A/B testing and causal inference

Moscow, Russia

❖ Developed machine learning models for the opening and closing of bank branches based on geodata and customer features. These models contributed to a 3% increase in the bank's profit❖ Created various customer response models tailored to different products for improved targeting. These models contributed to a 2% increase in the bank's profit❖ Significantly improved bank branch analytics and A/B testing processes and enhanced the company's grocery delivery ecosystem using customer logs and geo-visualization tools❖ Managed team members and established communication between different departments

Moscow, Russia

❖ Developed a ride time forecasting machine learning model using geo and customer data to enable more efficient pricing. This model resulted in a 4% increase in profit❖ Created a ride destination recommendation model to enhance the user experience, resulting in a 5% improvement in user activity metrics❖ Developed an uplift modeling framework for optimal targeting. This model improved promotional effectiveness and increased profit metrics by 2%❖ Conducted various product and pricing experiments that resulted in a 3% improvement in key metrics

Moscow, Russia

❖ Led courses on machine learning and data analytics as an additional activity

Moscow, Russia

❖ Developed various credit risk machine learning models, resulting in a 6% increase in profit metrics❖ Built data collection and predictive modelling pipelines❖ Analyzed data to assess the applicability of machine learning models and engaged with stakeholders

Moscow, Russia

❖ Conducted research in quantum physics utilizing computer modeling and mathematical calculations

Moscow, Russia

❖ Developed credit risk machine learning models and new customer features

Moscow, Russia

❖ Developed text classification and topic modeling approaches for the customer experience team, resulting in improved text matching and a 50% acceleration in decision-making