Abdulrashid Mukuev Email & Phone Number

Москва, Москва, Россия

* Spearheaded the analytics for performance marketing, overseeing data acquisition, preparation, and the strategic allocation of marketing campaigns and budget;* Developed a comprehensive monitoring and alert system for input data and pivotal indicators, utilizing DataStudio and Superset.* Designed five executive dashboards in DataStudio and Superset, facilitating daily and weekly oversight of the marketing team based on critical metrics and analyses;* Constructed an extensive dashboard in Superset for holistic analytics, focusing on client payback periods, acquisition costs, and lifetime value across various marketing channels;* Automated routine data uploads, reconciliation, and reporting processes for the performance marketing team using Python, SQL, and Airflow;* Instituted a robust framework for assessing A/B test outcomes for retargeting campaigns, leveraging Python and BigQuery;* Led a pivotal study analyzing the elasticity of primary metrics against marketing campaign parameters. This initiative resulted in a 20% reduction in fraud and a 15% increase in retention across performance channels.

Moscow, Russia

* Pioneered the development and deployment of time series models, leveraging econometric packages and machine learning, to evaluate the influence of TV advertising on lead generation. This innovation enabled a precise reallocation of digital channel expenses, enhancing the Customer Acquisition Cost (CAC) metric by 20%;* Enhanced and fine-tuned critical reporting systems and scripts across Oracle, BigQuery, and ClickHouse platforms. Notably, streamlined the report generation process for new clients, reducing the time from 5 hours to just 1 hour;* Formulated and tested hypotheses for A/B experiments, resulting in a 7% uplift in organic Click-Through Rate (CTR);* Architected and managed five automated dashboards in PowerBI and DataLens, focusing on the bank's pivotal KPI metrics;* Implemented alert mechanisms in Outlook and Slack, ensuring data accuracy in routine reports from BigQuery and Zeppelin using SQL and Python;* Spearheaded the development and maintenance of data transfer protocols between systems, such as migrating data from Oracle to ClickHouse, utilizing ProcSQL and Python;* Executed on-demand queries in Data Warehouse (DWH) systems with proficiency in SQL.

Moscow, Russia

* Pioneered the development of sophisticated econometric models with Python and Gretl, targeting the prediction of lead inflow through major online acquisition channels. Utilized advanced techniques such as SARIMAX and EGARCH for precise forecasting;* Crafted two comprehensive dashboards in Data Studio, shedding light on pivotal expenditure indicators, notably TV campaign outlays and costs associated with paid acquisitions;* Conceived and executed a Python-centric algorithm tailored for the enhancement of partner traffic acquisition, achieving a significant 30% boost in cohort conversion rates;* Streamlined pivotal data transfer scripts, accelerating the gathering of essential raw data for subsequent reports by a factor of four using SQL;* Steered the data engineering endeavors within the team, focusing on SAS and Oracle data warehouses, ensuring efficient data storage and retrieval processes.

Moscow, Russia

* Managed and refreshed routine reports utilizing Excel and SQL, ensuring timely and accurate data representation;* Executed on-demand queries within Oracle and SAS systems, catering to specific data retrieval needs;* Provided consistent support for existing dashboards in PowerBI and DataStudio, ensuring optimal performance and up-to-date insights.* Enhanced efficiency by optimizing existing scripts in Python and ProcSQL, leading to faster data processing and reduced computational overhead;* Played a pivotal role in supporting the primary data streaming processes between databases, ensuring seamless data flow and integrity.

Moscow, Russia

* Engineered a machine learning model using SkLearn and XGBoost to predict the medium-term attrition of the bank's corporate clients.* Conducted a comprehensive analysis to evaluate the influence of various factors on the likelihood of corporate client attrition, utilizing tools like SkLearn, Pandas, and Seaborn;* Demonstrated proficiency in executing SQL queries within Data Warehouse systems, specifically using HiveQL;* Managed data processing and preparation for routine reports, leveraging Python and Spark;* Upheld and enhanced existing workflows, ensuring version control through Git;* Authored detailed documentation on the bank's processes and reports, maintaining them in Confluence.

Master'S Degree, Computer Science, 8 / 10

Bachelor'S Degree, Economics, 4.3 / 5