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Senior Analyst

7 days ago

Manila, National Capital Region, Philippines Johnson & Johnson Full time

Job Role Overview

This role requires a highly skilled Senior Analyst, Data Intelligence to lead data analysis efforts to generate insights that drive data transformation initiatives and enhance business intelligence across the organization. You will be responsible for analyzing complex datasets, using statistical methods and advanced analytics to identify trends, patterns, and insights that influence strategic business decisions.

Responsibilities:

  1. Collaborate with multi-functional teams to define requirements and understand data needs, ensuring alignment with business objectives and driving impactful data initiatives.
  2. Design, develop, and optimize business intelligence dashboards and reporting tools that deliver clear and actionable insights to customers.
  3. Help and support data pipelines activities to ensure data integrity, availability, and usability across the organization.
  4. Monitor and report key indicators to ensure data reliability and integrity.
  5. Apply data science techniques, such as predictive modeling and machine learning, to advance analytical capabilities and provide innovative solutions to business challenges.
  6. Develop visualizations to communicate effectively with customers, simplifying complex information for diverse audiences.
  7. Stay abreast of industry trends and emerging technologies related to data analytics, data science, and business intelligence, assessing their applicability to enhance data intelligence.
  8. Collaborate with the Data and AI team on critical initiatives that enhance organizational data intelligence and analytics capabilities.

Requirements:

  1. Bachelor's degree or equivalent experience in Data Science, Computer Science, Engineering, Statistics, or a related field.
  2. Demonstrable experience (typically 5+ years) in data analysis, data science, advanced analytics, or a closely related field.
  3. Expertise in business intelligence tools (e.g., Tableau, Power BI) and advanced data visualization techniques.
  4. Proficient in SQL and other data manipulation tools, with strong analytical skills and experience in statistical analysis.
  5. Solid background in advanced analysis, including experience with predictive modeling, machine learning frameworks (e.g., TensorFlow, Scikit-learn).
  6. Solid understanding of data engineering practices, ETL processes, and data warehousing concepts.
  7. Strong problem-solving skills with a focus on deriving actionable insights from complex datasets.
  8. Excellent communication and presentation skills, capable of conveying technical information effectively to both technical and non-technical audiences.
  9. Demonstrable ability to work collaboratively within a team, manage multiple projects, and thrive in a fast-paced environment.
  10. Project management and agile methodologies are a must.