Data Analyst

Description

Join Winaxis LLC as a Data Analyst and play a crucial role in analyzing and interpreting complex data sets to drive key business decisions. As a Data Analyst at Winaxis LLC, you will be responsible for extracting, transforming, and presenting data in a meaningful way to support various projects and initiatives. This role is essential in providing valuable insights that will directly impact the company's strategic direction and growth.

As a Data Analyst at Winaxis LLC, you will work on a variety of projects ranging from market research and trend analysis to performance tracking and forecasting. Your analytical skills will be put to the test as you uncover patterns, trends, and correlations within the data to help optimize processes and improve overall business performance. This position offers a great opportunity to work remotely and collaborate with cross-functional teams to drive data-informed decisions.

Responsibilities:

• Collect, clean, and validate data to ensure accuracy and reliability.
• Analyze large datasets using statistical methods and data visualization techniques.
• Interpret data and present findings to key stakeholders in a clear and concise manner.
• Develop and maintain reports, dashboards, and data visualizations to track KPIs.
• Identify trends, patterns, and insights to support business objectives.
• Collaborate with teams to define data requirements for various projects.
• Conduct ad-hoc analysis to address specific business questions and challenges.
• Stay updated on industry trends and best practices in data analysis.

Requirements:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
• Proficiency in data analysis tools such as SQL, Excel, Python, or R.
• Experience with data visualization tools like Tableau, Power BI, or similar.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to work independently and collaborate effectively in a team environment.
• Excellent communication skills to convey complex findings to non-technical stakeholders.
• Knowledge of statistical methods and techniques for data analysis.
• Experience in interpreting and analyzing large datasets to extract insights.