Data Analyst I

Responsibilities

• Assist the TAP data team with the collection, organizing, and analysis of Thorlabs' various data sets.
• Develop and implement data models, algorithms, and statistical techniques to extract insights and generate reports, dashboards, and visualizations that inform data-driven decision-making.
• Conduct thorough data validation and quality assurance checks to ensure accuracy, integrity, and consistency of data.
• Interpret data findings and provide actionable recommendations to stakeholders, including business leaders and other relevant teams, to drive business performance and optimize operational processes.
• Collaborate with cross-functional teams to develop and execute data-driven strategies that align with business objectives.
• Stay up to date with industry trends, emerging technologies, and best practices in data analysis, and apply them to improve data-driven decision-making within the organization.
• Participate in data governance initiatives, including data documentation, data lineage, and data security, to ensure compliance with regulatory requirements and data standards.
• Determine and clarify strategic and operational issues via consultation.
• Track success of key initiatives (Corporate Initiatives, Kaizens, Product Line Reviews).
• Aid Managers/Supervisors in area performance capture and presentation.
• Aid in compiling and presenting information verbally, visually, and in writing.
• Occasionally lead operational training initiatives.

Qualifications

• Entry level to 1 year experience with data visualization best practices and the ability to create visually compelling reports, dashboards, and visualizations that effectively communicate complex data findings to non-technical stakeholders.
• Familiarity with data validation, data quality assurance, and data cleansing techniques to ensure data accuracy, integrity, and consistency.
• Bachelor's degree in Data Analytics, Business Analytics, Computer Science or related fields.
• Strong proficiency with data analysis techniques and tools, such as SQL, Python, Power BI, or Excel.
• Knowledge of data modeling, data warehousing, and data integration concepts.
• Ability to apply critical thinking and problem-solving skills to analyze data, identify patterns, trends, and correlations, and provide actionable recommendations for business decision-making.
• Excellent communication skills, both written and verbal, with the ability to effectively communicate complex data findings to diverse audiences.
• Experience with machine learning, predictive analytics, or data mining techniques is a plus.