Data Analyst

As a Data Analyst at Aspen One, your responsibilities include analyzing data from various resorts, cleaning and transforming data from the RTP point of sale system, and creating weekly business-driven financial reports. You'll define terminology for point of sale products, establish mapping tables for accurate reporting, and collaborate with other departments to identify best practices for data use.

To excel in the Data Analyst role at Aspen One, you will need a Bachelor’s Degree in Finance, Mathematics, Computer Science, or Statistics. Additionally, you should possess a minimum of 2 years of reporting experience, along with strong proficiency in Excel, PowerPivot, PowerBI, and SQL. Experience with RTP and strong problem-solving skills will also be advantageous.

Aspen One is committed to the professional development of its employees, including Data Analysts. The company provides opportunities for training and skill enhancement in data analysis tools and technologies, encouraging employees to stay updated on industry trends. Furthermore, a collaborative work environment allows you to learn from cross-functional teams, fostering personal growth.

At Aspen One, Data Analysts enjoy a dynamic and supportive work environment. The role often involves working at a desk with a mix of solitary data analysis and collaborative team efforts. The office itself offers a professional yet casual ambiance, and you're part of a culture that values inclusion, diversity, and innovation.

Data Analysts at Aspen One can expect a comprehensive benefits package, including health, dental, and vision insurance, flexible spending accounts, life insurance, and generous paid time off. Additional perks include an employee ski pass, 401(k) savings plan, and other exciting company benefits that foster a balanced work-life integration.

When approaching data analysis tasks as a Data Analyst, I begin by clearly defining the business question I need to answer. I gather relevant data from applicable sources, ensuring its accuracy and integrity. After cleaning and organizing the data, I apply various analytical techniques to draw insights, and then I present my findings in a structured and actionable manner.

In my previous roles, I have utilized SQL extensively to extract, manipulate, and analyze data from relational databases. I am comfortable writing complex queries to retrieve specific datasets and regularly used SQL to generate reports that informed strategic decision-making processes.

One challenging data project involved merging data from different sources with varying formats. I overcame this challenge by systematically cleaning and standardizing the datasets before merging them, ensuring accuracy. Collaboration with colleagues in cross-functional teams also aided in addressing data-related questions and provided additional insights.

To ensure data accuracy, I implement thorough validation checks throughout the data collection and analysis stages. This includes cross-referencing data from multiple sources, utilizing data profiling techniques, and leveraging automated tools to catch inconsistencies. I also document each step for future reference and auditing.

I frequently use tools like PowerBI and Tableau for data visualization because they allow for interactive and dynamic presentations of data insights. Visualizations enhance understanding and communication by transforming complex data into clear graphics, enabling stakeholders to grasp key points quickly.

When dealing with multiple projects, I prioritize tasks based on deadlines, project impact, and resource availability. I employ project management techniques to create a timeline for each task, ensuring that I allocate adequate time and attention to the most impactful projects while remaining flexible to accommodate any urgent requests.

I emphasize open communication and transparency when collaborating with cross-functional teams. Regular check-ins and progress updates help keep everyone aligned. I find it beneficial to engage team members early in the data analysis process to gather their insights and understand their specific needs, which fosters collaborative problem-solving.

I use several methods for cleaning and preprocessing data, including removing duplicates, filling in missing values, and standardizing formats. I employ statistical methods to identify and rectify anomalies while ensuring that the data is prepared for accurate analysis. Consistent documentation is crucial for replicating the cleaning process.

I stay updated with trends in data analysis and technology by subscribing to industry publications, attending webinars, and participating in relevant workshops. Networking with other data professionals and engaging in online forums also allows me to gain insights into emerging tools, techniques, and best practices in the field.

The most important skills for a Data Analyst include strong analytical thinking, proficiency in data manipulation tools like SQL and Excel, and the ability to communicate findings effectively. Additionally, problem-solving skills and a keen eye for detail are essential for uncovering insights and ensuring data accuracy in analyses.