The Data Analyst in the Enterprise Information Management (EIM) department will be responsible for analyzing, interpreting, and reporting on large datasets to support strategic decision-making within the organization. This role requires a strong analytical mindset, proficiency in data management tools, and the ability to communicate complex data insights to various stakeholders.

Data Collection and Analysis:

• Gather, process, and analyze large datasets from various sources like Oracle EBS, Demantra, ASCP, SFDC etc to support business objectives.
• Document and maintain reporting or analytical requirements.
• Should be able to present the documentation analysis to the stakeholders.

Reporting and Visualization:

• Create detailed reports and dashboards to communicate data findings and insights to stakeholders.
• Use data visualization tools (e.g. OAC Classic, OAC Advanced DV) to present complex data in a user-friendly manner.

Collaboration and Communication:

• Work closely with cross-functional teams, including IT and other Business operations, to understand data needs and deliver actionable insights.
• Communicate complex data analysis results clearly and effectively to non-technical stakeholders.

Continuous Improvement:

• Identify opportunities for process improvement and automation in data collection, analysis, and reporting.
• Stay up-to-date with industry trends, best practices, and emerging technologies in data analytics and enterprise information management.

Statistical Analysis and Modeling:

• Apply statistical methods to interpret data and identify trends, patterns, and relationships.
• Develop predictive models to support decision-making and strategic planning.
• Strong understanding of AI/ML methodology and able to interpret and expand the existing AI/ML Models.

Qualifications:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or equivalent relevant work experience. A master’s degree is a plus.
• Proven experience (2+ years) as a Data Analyst or in a similar role.
• Proficiency in data analysis tools and languages (e.g., SQL, Python, R).
• Experience with data visualization tools (e.g., OAC DV, PowerBI).
• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills.
• Ability to work independently and as part of a team in a fast-paced environment.

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