M Usman Malik

In this role, I worked on processing and cleaning clinical cancer data to ensure its quality and usability for product development. Leveraging advanced technologies, I integrated large language models (LLMs) such as PaLM2, OpenAI, and Gemini to enhance data utilization and insights. This position allowed me to bridge the gap between complex medical datasets and innovative AI-driven solutions, contributing to impactful healthcare products.

Dedicated Senior Data Analysis and Reporting Officer with a proven expertise in utilizing advanced tools and languages such as Spark, Python, and SQL for comprehensive data analysis and reporting. Proficient in designing and developing reports, dashboards, and visualizations using Power BI and Tableau, enabling stakeholders to make informed decisions. Experienced in data transformation, mining, and modeling, ensuring data accuracy and reliability. Skilled in effective communication of complex technical concepts and analytical findings to both technical and non-technical stakeholders. 𝐊𝐞𝐲 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: 1) 𝐃𝐚𝐭𝐚 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐒𝐜𝐫𝐢𝐩𝐭𝐬: -> Developed customized scripts to read data files and perform necessary transformations, enabling seamless analysis in Power BI and Excel. -> Automated data processing tasks, improving efficiency and accuracy in reporting. 2) 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐚𝐧𝐝 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: -> Implemented advanced data analysis techniques to provide insights on sensor-generated data, identifying efficiency patterns and areas of improvement. -> Created interactive dashboards highlighting efficiency metrics, allowing stakeholders to track efficiency losses and optimize processes effectively. 3) 𝐂𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐒𝐲𝐬𝐭𝐞𝐦 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: -> Established a centralized NoSQL database system to store and backup all data from various sources. -> Ensured seamless accessibility to historical and real-time data, empowering teams to retrieve information for analysis at any given time. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐯𝐞 𝐖𝐨𝐫𝐤 𝐚𝐧𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: -> Collaborated with cross-functional teams to gather requirements and define data storage and retrieval processes. -> Effectively communicated analytical findings through visual storytelling, utilizing tools like Power BI, ensuring understanding among diverse stakeholders.

In my role as a data engineer, I was responsible for reading data from Kafka topics, which contained information extracted from various social media platforms. My tasks included transforming this data and storing it in databases and Kafka topics. The data I worked with comprised images, videos, and textual data. I was tasked with downloading and updating the paths for media files locally, allowing for efficient access without redirection to social media platforms. Additionally, I interfaced with machine learning teams, calling ML algorithms APIs, and managed the data responses, ensuring seamless integration and storage in the database. 𝐃𝐚𝐭𝐚 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Designed and implemented efficient data processing pipelines using Pyspark, Hadoop, and Kafka. 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐞𝐝 𝐒𝐲𝐬𝐭𝐞𝐦𝐬: Developed and maintained distributed systems for real-time data ingestion, transformation, and storage using Kafka. 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐏𝐫𝐨𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲: Wrote efficient and scalable Python code for data analysis, data processing, and machine learning tasks. 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐀𝐬𝐬𝐮𝐫𝐚𝐧𝐜𝐞: Implemented data quality checks and monitoring tools to ensure data accuracy and completeness. 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Collaborated effectively with data scientists and analysts, understanding their data needs and enabling access and analysis. 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Stayed up-to-date with the latest tools and technologies in the data engineering field, ensuring the continuous improvement of the data pipeline.

-> Design and develop software applications using Python programming language. -> Write clean, maintainable, and efficient code that meets the requirements and specifications. -> Debug and fix any coding issues and improve existing applications. -> Test and optimize software performance to ensure high-quality output. -> Collaborate with cross-functional teams including software developers, project managers, and stakeholders. -> Analyze user requirements and implement software solutions to meet business needs. -> Participate in code reviews, design and architectural discussions, and software development life cycle processes.