Senior Data Analyst

Key Responsibilities

• Data Analysis & Insight Generation:

  Conduct in-depth analysis of large and complex datasets to identify trends, patterns, and anomalies. Translate raw data into clear, concise, and actionable insights that address key business questions.

• Data Manipulation & Transformation:

  Expertly "slice and dice" data using advanced functions and features in Google Sheets or Microsoft Excel to prepare data for analysis, build models, and create reports.

• Reporting & Visualization:

  Develop and maintain comprehensive dashboards, reports, and presentations that effectively communicate analytical findings to various stakeholders, including senior leadership.

• Problem Solving:

  Proactively identify business problems and opportunities, and leverage data to propose solutions and strategies.

• Stakeholder Collaboration:

  Work closely with cross-functional teams (e.g., Marketing, Operations, Product, Finance) to understand their data needs and provide data-driven support for decision-making.

• Data Quality & Governance:

  Contribute to ensuring data accuracy, consistency, and integrity across various data sources.

• Methodology & Innovation:

  Continuously explore and implement new analytical techniques and tools to enhance the team's capabilities and efficiency.

Qualifications

Required

• Experience:

  Progressive experience in a data analytics role, with a proven track record of delivering impactful data-driven insights.

• Analytical Mindset:

  Demonstrated strong analytical and problem-solving skills, with an innate curiosity and ability to break down complex problems into manageable components.

• Data Manipulation Expertise:

  Exceptional hands-on proficiency with either Google Sheets or Microsoft Excel (advanced functions, pivot tables, VLOOKUP/XLOOKUP, conditional formatting, data validation, charting, etc.) is a must.

• Data Slicing & Dicing:

  Proven ability to effectively manipulate, transform, and analyze large volumes of data from various sources to uncover meaningful patterns and relationships.

• Communication Skills:

  Excellent verbal and written communication skills, with the ability to articulate complex analytical concepts to non-technical audiences clearly and concisely.

• Attention to Detail:

  Meticulous attention to detail and a commitment to data accuracy and integrity.

• Proactiveness:

  Self-motivated, proactive, and able to work independently as well as collaboratively within a team environment.

Preferred Qualifications (Nice to Haves):

• Experience with SQL for data querying and extraction.
• Experience with statistical analysis and modeling (e.g., Python, R)