Product Owner

Introduction:

The candidate has a strong background in data science, product ownership, and data analytics, with significant experience in driving product development, campaign management, and forecasting using advanced data techniques. They have expertise in machine learning, big data technologies, and statistical analysis, having worked on projects involving personalized direct mailing, customer segmentation, and marketing insights. Additionally, they have experience with data integration, forecasting, and HR analytics, using tools such as SAS, SQL, and Python. Their skills extend to SaaS telemetry, Agile and Lean methodologies, and reporting tools like Power BI and Tableau. With a robust understanding of both the technical and business aspects, they have led teams of data engineers and analysts, working closely with cross-functional teams to deliver actionable insights and drive data-driven decision-making. The candidate has also contributed to academic research, with publications in reputable journals, demonstrating their proficiency in data analysis and research methodologies.

Responsibilities:

• Organized and prioritized development projects based on SaaS telemetry.
• Created product roadmaps and managed backlog prioritization.
• Managed delivery risks and issues for data-related projects.
• Led a feature team consisting of data analysts and data engineers.
• Acted as an interface between sales, development, and data teams.
• Organized and facilitated team ceremonies such as sprint planning, daily scrums, retrospectives, and refinement meetings.
• Conducted testing of products to identify and implement functional improvements.
• Analyzed and optimized personalized direct mailing campaigns, including A/B testing and execution.
• Provided insights into mass marketing campaigns and customer segmentation.
• Implemented integrated forecasting and planning solutions for sales, marketing, and finance teams.
• Developed an ELT layer for commercial reporting, leveraging technologies like SAS DI, SQL, and Netezza.
• Built and implemented machine learning models to detect absenteeism and assess its drivers for HR analytics.
• Designed and developed algorithms, performing statistical data analysis and interpretation for research purposes.
• Delivered oral and poster presentations at international and national conferences.
• Provided training on Microsoft Office tools to individuals with diverse backgrounds.
• Assisted in troubleshooting and developing GIS-based telecommunications network solutions.