Chioma Ibenjo

Responsibilities:

• Converted, cleaned, analyzed, organized, and documented large data files (10,000 - 2 million records).
• Performs data Visualizations, data extract from different databases to create complex reports and present it to clients.
• Conduct big data analysis and data mining on laboratory test data as large as 10 billion records using Netezza, Hadoop and Datameer.
• Use ETL tools for data integration, use raw data, extract the information required for analysis, coordinate with ETL teams for data transformation and format data to serve business needs, and load it to a data warehouse.
• Design, built and deployed a set of python modeling APIs for customer analytics, which integrate multiple machine learning techniques for various user behavior prediction.
• Build and productionize predictive models on large datasets by utilizing advanced statistical modeling, machine learning, or other data mining techniques using Python, R, Scala and/or Java, MapR, Spark.
• Explore complex data using Datameer, implement data quality measure and secure data for faster insights at LabCorp.
• Use personalization to rapidly integrate, transform, discover, and operationalize datasets to meet business needs.
• Establish an analytical pipeline in Datameer to streamline the analytical process.
• Handle data request and perform analysis using tools like Datameer and Oracle SQL Developer.
• Write complex report criteria to fulfill Clinical Trials data requests and review with business teams.
• Develop and train resources on ICD9 – ICD10 cross-walk tool, conduct data mapping and review errors.
• Lead the team of data scientists specializing in a range of statistical, natural language processing-NLP, and machine learning techniques
• Created complex visualizations using tableau for business requirements.
• Design and implement end-to-end systems for Data Analytics and Automation, integrating custom visualization tools using R, Tableau,Power BI.
• Query data from Business Intelligence and database to create standardized reports.
• Write and execute complex SQL queries to fetch data from different databases according to the business requirements.
• Successfully interpreted data in order to draw conclusions for managerial action and strategy.
• Used statistical techniques for hypothesis testing to validate data and interpretations.
• Conducted research using focus groups and increased efficiency by 11% due to the findings.