About
Alexander Modestov is a highly accomplished AI/ML and Data Analytics Expert with 10 years of experience spearheading robust data infrastructure development, implementing AI-driven solutions, and optimizing complex data pipelines. He excels at leading high-performing teams to deliver actionable insights, consistently driving substantial improvements in user engagement, conversion rates, cost savings, and overall productivity. His expertise spans AI-driven solutions, data warehousing, A/B testing, and ML-powered systems, positioning him as a strategic asset for data-intensive organizations.
Work
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Summary
Led the establishment of a full-scale analytics department and developed advanced AI/ML solutions for product analytics, driving significant improvements in data infrastructure and communication analysis.
Highlights
Established a full-scale analytics department from inception, implementing Amplitude, Branch.io, and Looker, and designing a scalable DWH/ETL infrastructure.
Developed an AI-driven communication analysis tool for an EdTech startup, automating transcription, semantic parsing, and seller performance recommendations using GenAI (OpenAI, Claude, Mistral, Llama).
Designed and implemented a video analytics pipeline utilizing YOLO and custom ML models to detect and classify specific behavioral events in video streams.
Created a Retrieval-Augmented Generation (RAG) system for an internal AI assistant, streamlining onboarding and knowledge transfer for new employees.
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Summary
Spearheaded the development of AI-driven solutions and optimized data pipelines, significantly enhancing customer engagement and decision-making efficiency.
Highlights
Developed AI-driven RAG systems using LLMs (OpenAI, Claude, Mistral, Llama) for automated conversation analysis, achieving an 80% reduction in vendor costs and a 50% boost in sales productivity.
Led a team of analysts and data engineers to deliver data-driven insights, significantly improving decision-making efficiency and operational effectiveness.
Built and optimized data pipelines (Apache Airflow, dbt) and cloud-based AI tools, accelerating data analysis by over 50% and improving report quality by 25%.
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Summary
Expanded and led a high-performing product analytics team, driving data-driven decision-making and enhancing key user metrics for multiple internal products.
Highlights
Expanded and led a 10-member product analytics team, tripling its size, and organized processes to analyze 8 internal products, fostering a high-performing, data-driven environment.
Conducted 20+ comprehensive A/B tests, encompassing hypothesis creation, experimental design, and in-depth analysis, which led to 4 key initiatives improving user retention and engagement.
Crafted and implemented customized strategies for five distinct products, achieving substantial improvements: a 30% increase in NPS, a 20% boost in conversion rates, and a 20% rise in user engagement.
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Summary
Built and managed the analytics framework for a portfolio of over 25 services, delivering critical insights and driving customer journey improvements.
Highlights
Built and managed the analytics framework for 25+ services, defining KPIs (revenue, churn rates, active user engagement) to deliver critical business insights.
Designed and executed A/B tests to enhance customer journeys, achieving a 30% reduction in churn rates and fostering stronger customer loyalty.
Led intercompany innovation by implementing advanced analytical frameworks across interdisciplinary teams, reducing the time required to obtain analytical results and measure new feature metrics by 25%.
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Summary
Developed and deployed AI/ML models for personalization, recommendation, and fraud detection, significantly improving user engagement and platform security.
Highlights
Developed AI-powered personalization and recommendation models, increasing user engagement by 20% and enhancing user experience.
Created and deployed robust ML-based fraud detection systems, proactively preventing fraudulent activities and significantly improving platform security.
Provided strategic direction and technical leadership for data science initiatives, overseeing the successful deployment and maintenance of critical AI/ML solutions.
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Summary
Implemented Big Data solutions and deployed automated ML-based ranking models to enhance conversion rates.
Highlights
Implemented Big Data solutions (Apache Spark, Python, H2O) for ML-powered scoring and ranking systems, optimizing data processing efficiency.
Deployed automated ML-based ranking models, significantly increasing conversion rates by 30% through data-driven optimization.
Conducted in-depth business analysis to identify key opportunities for data science application, translating complex data into actionable insights for stakeholders.
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Summary
Designed and built AI-driven optimization systems for cost reduction and logistics efficiency, delivering significant client satisfaction.
Highlights
Designed AI-driven cost optimization systems for Eurasian Resources Group, achieving over $1M in annual savings.
Built AI-powered logistics optimization models, improving efficiency by 50% and reducing costs by 18%.
Provided strategic, client-focused solutions through expert consultations, driving high client satisfaction and loyalty.
Languages
English
Skills
AI & Machine Learning
Anthropic, RAG Pipelines, AutoGen, CrewAI, DeepSeek, LangChain, Gemini, LangGraph, Llama, LlamaIndex, OpenAI, Mistral, Multi-Agent Systems, Qwen, Personalization Models, Recommendation Systems, Fraud Detection, Cost Optimization, Logistics Optimization, Ranking Models.
Analytics & Data Engineering
Airflow, A/B Testing, Apache Spark, Databricks, dbt, Python, Docker, FastAPI, Gradio, MLflow, Power BI, Snowflake, SQL, Statistical Analysis, Streamlit, Tableau, Data Warehousing, ETL Infrastructure, KPI Definition, Business Intelligence.