Senior Data Analyst / Data Scientist

Data Extraction and Analysis:

• Collect, clean, and analyze large datasets related to operations, commerce, user behaviors, retention, operational efficiencies, user experience, employee experience, redundancies, and more.
• Utilize statistical methods and tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics.

Commercial and Non-Commercial Insights:

• Focus on commercial data (marketing, sales) to provide insights on customer acquisition, retention, revenue growth, and market trends.
• Analyze non-commercial data (operations, maintenance, customer advocacy, inventory) to identify areas for operational improvements and efficiency gains.
• Reporting and Visualization:
  • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to management and stakeholders.
  • Present complex information in a clear and concise manner, making data accessible and understandable to non-technical team members.

Proactive Insight Generation:

• Go beyond management's requests to identify and explore data-driven opportunities and challenges not previously considered.
• Provide inferential insights that can lead to strategic advantages and operational enhancements, highlighting areas that may not be immediately apparent.

Industry and Market Analysis:

• Gather and analyze industry data to understand market dynamics, competitor performance, and external factors affecting the business.
• Use external data sources to augment internal data, providing a comprehensive view that aids in strategic planning and decision-making.

Data Integrity and Compliance:

• Ensure data accuracy and integrity by performing regular audits and validation checks.
• Adhere to data privacy regulations and company policies when handling sensitive information.

Collaboration and Accountability:

• Work closely with cross-functional teams, including marketing, operations, maintenance, HR, and management, to support their data needs.
• Help teams understand the implications of data insights for their areas, promoting data-driven decision-making across the organization.
• Contribute to holding teams accountable by providing transparent and actionable data.

Education and Experience:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Minimum of 3 years of experience in data analysis, business intelligence, or a similar role.
• Proficiency in data analysis tools and languages such as SQL, Python, R, and experience with data visualization tools like Tableau or Power BI.
• Familiarity with data warehousing concepts and ETL processes.

Skills and Abilities:

• Analytical Expertise: Strong analytical skills with the ability to interpret complex datasets and translate findings into actionable insights.
• Commercial Acumen: Understanding of both commercial (marketing, sales) and non-commercial (operations, maintenance) aspects of the business.
• Technical Proficiency: Experience with statistical analysis, predictive modeling, and data mining techniques.
• Communication Skills: Excellent verbal and written communication skills, with the ability to present data findings to non-technical audiences effectively.
• Problem-Solving: Proactive in identifying issues and opportunities within the data, providing solutions that align with business objectives.
• Attention to Detail: Meticulous in ensuring data accuracy and integrity.
• Industry Awareness: Knowledge of industry trends and the ability to leverage external data sources for comprehensive analysis.

Personal Attributes:

• Resilience: You believe there's always a solution and persistently seek answers through data.
• Growth Mindset: Fully committed to personal and professional development, staying updated with the latest data analytics tools and methodologies.
• Profitability Focus: Understand how data insights can drive profitability and operational efficiency.
• Results-Oriented: Dedicated to delivering high-quality outcomes that make a tangible impact.
• Long-Term Vision: Provide data solutions that contribute to lasting success and sustainability.

Personal Competencies:

• Curiosity and Innovation: A natural inclination to explore data creatively, uncovering hidden patterns and insights.
• Integrity and Ethics: Maintains confidentiality and handles sensitive data responsibly.
• Collaboration: Works effectively with various teams, fostering a culture of data-driven decision-making.
• Adaptability: Comfortable navigating changing priorities and adapting to new analytical tools or methodologies.

On-the-Job Competencies:

• Data Modeling and Interpretation: Expertise in creating models that predict trends and inform strategic decisions.
• Data Visualization: Ability to present data in engaging and understandable formats.
• Business Intelligence: Apply data insights to improve business processes, customer experience, and operational efficiency.
• Technical Proficiency: Skilled in using advanced analytical tools and staying abreast of technological advancements in data analytics.