Data Scientist

Job Overview

• Implement business process improvements - automating manual processes, optimizing data deliverredesigningirestructuringure data and process flows for more efficiency.
• Develop expertise and aim to become a subject matter expert on the entire data, analysis, cs, and process automation ecosystem.
• Bridge process and technology gaps with innovative solutions using a variety of tools (e.g. Power Automate, Python, PowerApps, Selenium, SQL, UI Pa, etc.)
• Develop and maintain ETL (Extract, Transform, Load) processes for data management.
• Create visually appealing, intuitive, and insightful dashboards and reports using data visualization tools (e.g. Power BI, Tableau).
• Utilize statistical techniques to solve business problems and provide insights.
• Present findings and recommendations to stakeholders clearly and concisely.
• Collaborate with cross-functional teams to understand their data and process needs and provide analytical and digitization support.
• Collaborate with DBAs,, IT and Architecture teams as required
• Be heavily involve the d in development and testing of newly integrated data sources and/or environments
• Document data processes, methodologies, and analysis techniques for future reference and training purposes.

What your background should look like:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Industrial Engineering, or a related field.
• 2+ years of experience as a Data Analyst, Digital Transformation Analyst, or in a similar analytical/technical role preferably in a procurement or supply chain environment.
• Experience with automation tools such as Power Automate, PowerApps, UI Path, Python, Selenium, etc.
• Experience creating and managing databases in AWS, SQL Server, Oracle, etc., and working with APIs to integrate systems.
• Possess transferrable programming skills in any language (e.g. Python, C++, JavaScript, etc.)
• Proficiency in SQL for database querying and manipulation.
• Experience with statistical analysis software (e.g., R, Python).
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of Excel at an advanced level (Power Query, macros).
• Demonstrable willingness to learn new tools and technologies.
• Strong analytical and critical thinking abilities.
• Ability to explain technical processes to non-technical audiences.
• Attention to detail and a proactive approach to problem-solving.
• Ability to manage multiple projects and meet deadlines in a fast-paced environment.
• Knowledge of machine learning algorithms and data modeling techniques.

Competencies