Senior Data Scientist
ExxonMobil
Total years of experience :14 years, 3 Months
• Client / Stakeholder Automation: Designed and implemented automated data-collection processes, reducing manual efort by 40%, resulting in improved eficiency and accuracy of training-related data gathering.
• Project Governance and Controls: Developed and maintained a secure and integrated data repository/database, ensuring data integrity and availability to support organizational objectives, achieving a 99.9% uptime.
• Training Program Outcomes: Conducted predictive analysis models using Python, forecasting training program outcomes with a 90% accuracy rate, aiding in proactive decision-making for program improvements.
• Analytical Programming: Leveraged statistical programming tools such as R to provide analytical findings and recommendations, contributing to a 20% improvement in training program eficacy and resource allocation.
• Value Engineering: Applied quantitative and qualitative research methods to evaluate industrial and professional training programs, identifying areas for improvement and optimizing resource allocation, resulting in a 20% increase in training ROI.
● Advanced Dashboard KPI: Created and managed an advanced system of dashboards using Power BI, tracking key performance indicators (KPIs) for training programs, leading to a 25% increase in data-driven decision-making efficiency.
● Employee Performance Tracking: Led pilot studies and experimental designs, evaluating new training interventions, resulting in a 15% increase in training effectiveness and employee performance.
● Effective Risk Management: Utilized SQL to validate and enhance the quality of training-related data, reducing data discrepancies by 30%, leading to more reliable analytical outcomes.
● Strategic Project Planning: Led strategic planning initiatives for data-driven projects, aligning organizational objectives with actionable plans, resulting in a 30% increase in project success rates and stakeholder satisfaction.
● Data BI Visualization: Implemented business intelligence tools like Tableau to visualize training analytics, facilitating clear and concise communication of insights to stakeholders.
• Release Management: Orchestrated release management processes, ensuring smooth and eficient deployment of data analytics solutions, leading to a 25% reduction in post-release defects and system downtimes.
• Data Validation: Designed and implemented data validation processes, ensuring accuracy and reliability of training-related data, reducing data errors by 25%.
• Quality Monitoring: Established robust quality monitoring mechanisms for data analytics pipelines, enforcing adherence to industry standards and best practices, resulting in a 20% improvement in data accuracy and reliability.
• Global Data Integration: Implemented advanced data integration strategies for global datasets, synchronizing diverse data sources, resulting in a 40% reduction in data silos and improved cross regional decision-making capabilities.
• Optimized Engineering Workflows: Designed workflow optimizations within engineering teams, leveraging technical expertise to enhance eficiency and reduce project timelines, resulting in a 15% improvement in overall project delivery.
• Assessment of Data: Conducted comprehensive data audits and assessments, identifying opportunities for process improvement and optimization, leading to a 30% increase in data eficiency and performance.
• Data Training Programs: Developed and delivered customized data training programs for client teams, empowering them with essential data skills and knowledge, resulting in a 20% improvement in data literacy within client organizations.
• Performance Monitoring: Implemented performance monitoring frameworks for data solutions, enabling real-time tracking of key metrics and KPIs, resulting in a 15% increase in operational eficiency and performance optimization.
• Risk Management: Developed and implemented customized risk mitigation strategies, tailored to the specific needs and complexities of each consulting project, resulting in a 30% reduction in potential disruptions. Integrated risk response plans into the overall project management framework.
• Cross Functional Collaboration: Collaborated with cross-functional teams to ensure seamless integration of data solutions into existing systems and workflows, minimizing disruptions and maximizing ROI.