Abdulhakeem – SQL, Python, Machine learning

The company's team is best-in-class across drug selection, drug development, and tech.

• Optimized and stabilized a complex CI/CD workflow supporting Dagster-based ELT and ETL pipelines, improving deployment reliability and developer productivity;
• Resolved Snowflake MFA and authentication issues, reducing access friction and improving platform security and operational continuity;
• Designed and implemented Snowflake roles, security policies, and external integrations using Terraform, enabling consistent and scalable infrastructure-as-code practices;
• Refactored, optimized, and extended multiple production data pipelines, improving performance, maintainability, and data quality across the platform.

A custom CRM for outsource staff to log their hours and many of their administration-related tasks via Teams.

• Increased staff engagement and management productivity across company.

Abdulhakeem worked on building the dwh and data pipelines, implementing and deploying an AI dynamic pricing and marketing project, and achieving a staggering 189% year-on-year growth in digital channel revenue.

• Built Consistent Data Pipelines Using Dbt;
• Led the development of an AI-driven dynamic pricing and marketing system;
• Spearheaded the integration of advanced algorithms to optimize pricing strategies;
• Achieved 189% year-on-year growth in digital channel revenue;
• Coordinated cross-functional teams to ensure seamless implementation;
• Monitored and fine-tuned the AI pipelines for continuous improvement;
• Deployed and served models;
• Analyzed data and provided actionable insights to drive revenue growth.

This platform helps artists distribute their music, connect with fans, and collect royalties.

• Redesigned data warehouse, reducing cost by 76% by refactoring;
• Built and deployed a music transcription model;
• Increased engagement metrics of companies' songs on the music transcription services by 12pp.

The first Connected TV, measuring & managing platform designed to combine the impact of TV with the performance of digital advertising.

• Built Data Pipelines for a couple of marketing metrics;
• Integrated Data from Different source;
• Exposed Data into Looker;
• Aligned with different stakeholders to collect multiple requirements.

Mexican digital financial services platform allows users to manage their money in a secure and personalized way from their smartphone. As a Data Engineer, Abdulhakeem was recruited to collaborate with business stakeholders making the data available to them and matching their business realities.

• Refactored existing data pipelines;
• Maintained and onboarded employees to DBT;
• Built new Data pipelines to help businesses solve problems;
• Defined and streamlined workflow processes.

Abdulhakeem's involvement with the product was on a freelance project which involved work aimed at helping the leading e-commerce marketplace (under NDA) understand its customers better and build machine learning models to proactively cluster the customers and upsell them.

• Supported the product in a remote role as a Data Scientist;
• Built a Customer Clustering model that helped predict churning and active customers
• Mined the Process of Shopping on an e-commerce shop, thereby providing the stakeholders with insight that helps change presumptions and improve the website design and marketing strategies.

Leading Fashion Marketplace in Europe. Abdulhakeem was brought into one of the operations teams to redesign its reporting layer with a focus on the availability of data.

• Collaborated with business stakeholders to understand their Data needs for different project roadmaps Refactored and Redesigned existing data pipelines to ensure 3x higher performance per model;
• Built new data pipelines for new data sources;
• Improved Data Quality & Availability;
• Applied machine learning concepts in building a 90% accurate model for capacity planning thereby leading to a 50% reduction in cost per assortment production.

The largest bank in West Africa. Abdulhakeem was one of the first Data Analysts in the Bank and joined the team created for building the bank's data warehouse.

• Applied knowledge of data modeling and statistical analysis to note trends and draw conclusions;
• Developed Tableau Dashboards with marketing metrics used to determine inefficiencies, opportunities, and areas for improvement.
• Tracked, analyzed, and interpreted trends in operational data using Python;
• Gathered, organized, and input information into a digital database;
• Generated reports detailing findings and recommendations.