Data Analyst

Job Summary

The  Data Analyst II is responsible for collecting, analyzing, and interpreting complex data sets to provide valuable insights and support data-driven decision-making. The incumbent will utilize strong skills in data manipulation, statistical analysis, and data visualization to enhance understanding of key trends and patterns. The Data Analyst II will contribute to driving data insights, improving decision-making processes, and enabling the organization to achieve its goals through data-driven strategies.

Essential Duties and Responsibilities

• Data Analysis: Perform advanced data analysis, including data cleansing, data transformation, and statistical modeling, to extract meaningful insights from large and complex datasets.
• Data Interpretation: Translate data findings into clear and concise reports, dashboards, and presentations, and effectively communicate key insights and recommendations to both technical and non-technical stakeholders.
• Data Visualization: Design and create visually appealing and interactive data visualizations using industry-leading tools (e.g., Tableau, Power BI) to facilitate data-driven decision-making and enhance data understanding.
• Data Management: Develop and implement data management strategies, ensuring data integrity, accuracy, and consistency, and establish best practices for data collection, storage, and analysis.
• Reporting and Documentation: Prepare comprehensive reports, documentation, and documentation guidelines to ensure that analytical processes and findings are properly documented and reproducible.
• Collaboration: Collaborate with cross-functional teams, including business stakeholders, data engineers, and data scientists, to identify data requirements, extract relevant information, and align analytical efforts with business objectives.
• Process Improvement: Continuously identify opportunities to optimize data collection, analysis, and reporting processes, and contribute to the development and implementation of scalable data analytics solutions.
• Quality Assurance: Conduct rigorous quality assurance checks to validate data accuracy, reliability, and validity, and troubleshoot data-related issues as they arise.
• Industry Knowledge: Stay up to date with the latest trends and advancements in data analytics, including emerging tools, techniques, and best practices, and proactively apply new knowledge to improve analytical processes.

Knowledge, Skills & Abilities

• Excellent computer skills (MS Word, Excel, PowerPoint).
• Excellent oral, written, and customer service-oriented communication skills, with the ability to present complex findings in a clear and concise manner to both technical and non-technical stakeholders.
• Excellent organizational skills with the ability to respond to and coordinate multiple activities simultaneously under short time frames.
• Excellent and demonstrated critical thinking ability with keen attention to detail.
• Must be able to work both collaboratively and independently and communicate/present professionally with internal and external customers.
• Excellent problem-solving skills and the ability to work independently or in a team setting, actively participate in discussions, and contribute to the achievement of team goals.
• Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights. Familiarity with statistical concepts and methods (e.g., hypothesis testing, regression analysis) is essential.
• Strong attention to detail and a commitment to data accuracy and quality. Ability to identify data anomalies, perform data validation, and conduct thorough quality assurance checks.
• Flexibility to work in a fast-paced and evolving environment, with the ability to prioritize and manage multiple tasks and projects simultaneously.
• Understanding of business operations and the ability to align data analysis efforts with organizational objectives and key performance indicators.

Education, Experience, & Licensing Requirements

Education

• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or related discipline or an equivalent combination of education and experience required. A master's degree preferred.

Experience

• Three (3) years of experience as a Data Analyst, preferably in a business or corporate setting.
• Experience working with large datasets and conducting statistical analysis is required.
• Proficiency in data manipulation and analysis using SQL, Python, R, or similar programming languages.
• Strong knowledge of data visualization tools such as Tableau, Power BI, or similar tools. Experience with data modeling and machine learning techniques is a plus.

Travel Requirements

• Employee will work remotely from a home-based office. Infrequent travel may be required.