Nazym Satbekova

• Developing a chatbot web application, leveraging a tech stack with LLMs, OpenAI, LangChain, and other advanced technologies
• Actively shaping and implementing various product features for b2b chatbot platform including implementation of rag, classifiers based on fine-tuning of LLMs and collaborating closely with developers, ensuring the seamless deployment of AI-powered solutions

• Collaborated with country teams to develop machine learning models improving lead-agent matching algorithms, leading to enhanced conversion rates. Contributed to the automation efforts of the associated API service for increased operational efficiency
• Teamed up with the Insurance product group to develop dashboards for their use by creating an NLP-based text review classification algorithm, utilizing motor insurance reviews scraped from external platforms

• Engineered metrics dashboards by extracting and clustering driving behavior from clients' auto tracking/GPS data
• Developed and delivered customized BI/DS/ML educational programs for clients (local state organizations), utilizing a range of tools including Tableau, Knime, Python, other BI analytics platforms and leveraging clients' data for further practical applications. Additionally, implemented BI reporting systems within PowerBI Server solutions, overseeing the management and enhancement of clients' PowerBI reports

• Developed Deep Learning & Machine Learning models in PyTorch and scikit-learn for automating advert moderation on an ecommerce website/app, achieving a 65% automation rate through a complex NLP project
• Designed, developed, and managed big data-driven predictive modeling pipelines for fraud detection on an apartment rental website/app, attaining a 99% precision rate using classic machine learning techniques
• Conducted feature engineering on structured and semi-structured data from various sources, including messengers, text, and images, to evaluate the feasibility of machine learning applications across CV and NLP projects
• Collaborated seamlessly with developers, the product team, and end users to deliver data products as efficient microservice solutions deployed to production. Took ownership of ML projects, ensuring widespread adoption and effectiveness

• Conducted customer segmentations for cards and personal loans, utilizing classic ML models to enhance targeted marketing campaigns in retail banking
• Applied analytics and data mining to address business challenges in the medium-small businesses' sector, focusing on new client acquisition
• Collaborated with developers, business managers, and data consultants to formulate business requirements and assisted in building data warehouses, structured reports for executive decision-making, mentored team members on SPSS and data mining techniques

Applied ML and data mining for client segmentation in hard collection, optimizing debtor portfolio distribution across key processing channels, including call centers, field managers, and collector companies. Established analytical pipelines to monitor improvements, analyze loan payment patterns, and assess the efficacy of customer processing channels taking ownership of KPI metrics for hard collection analytics. Collaborated with developers, product owners to identify and align analytical requirements with project needs, formulating data warehouse (DWH) requirements

Provided BI and analytics support for a 500K user base, conducting post-analyses on marketing efforts including customer churn, retention, acquisition, loyalty programs, and up-sales/cross-sales. Insights informed stakeholder presentations and drove revenue and user base growth