Data Analyst: Real Estate @ Mynd

About us:

What do we have in Mynd?

How about the industry’s first mobile app that gives you up-to-the-minute performance data on the fly, for on-the-go control of your real estate investment, wherever you are. You instantly know when rents are paid and have a snapshot of profits whenever they’re needed. Owners can also review maintenance requests and approve expenses as they happen, and get alerts about things like local market trends.

This radical departure from property management also includes unparalleled service from the Mynd team, led by Doug Brien and Colin Wiel, who have our customers best interests, at all times.

The role:

Mynd is looking to add our 1st Data Analyst to our growing team. Through our technology driven business platform, Mynd is making residential property management smarter, simpler and more profitable. We do this by bringing best-in-class systems, use of data, automation and AI, which will enable us to operate efficiently at scale and become a national brand. An essential part of our plan is to decouple the traditional property manager - property relationship and instead build a task-based operating platform to more efficiently manage property management workflows, which allows us to measure each task and optimize performance over time. Mynd’s ultimate goal is to create a highly efficient operating platform thus allowing us to run the business for less, pass on some of the savings to owners and still generate attractive margins

As part of the data analytics team, the you will manipulate and analyze data from varying sources, identify trends and patterns and provide meaningful, relevant and insightful analysis related to real estate investing and property management. This content will take various forms including written narratives in Mynd’s articles and reports, visual content included in presentations and excel based prototype for product and engineering teams.

Our ideal candidate has:

• Bachelor’s degree in Statistics, Mathematics or another quantitative degree.
• Proficiency in Excel (pivots, vlookups, nested If statements, VBA macros)
• Knowledge of SQL and common data GUI (e.g. Looker, Tableau etc.) desirable
• 3-5 years of work experience in highly analytical role
• Real Estate experience is preferred
• Highly analytical and creative thinker comfortable working with ambiguity
• Willing to form your own opinions based on data and then test them
• Must be self-directed, organized and detail oriented
• Startup experience a plus

You will:

• Acquire, clean, and structure data from multiple sources and analyze it to draw insightful conclusions, trends and correlations
• Analyze Mynd’s operating data to identify trends/patterns which could be used to improve operational efficiency
• Use data analysis, data visualization and predictive modeling to solve complex problems, enhance existing products and develop new product offerings
• Generate well-written, relevant and thought provoking analysis, commentary and visualizations on residential property management and key markets
• Champion a data-driven culture, bringing an analytical and A/B testing approach to decision-making at Mynd
• Work closely with engineering team to support the selection and development of analytics tools that will empower every employee with access to data
• Work closely with Product Managers and the Marketing team to develop hypotheses and implement solutions that optimize funnel conversion, acquisition channels and lower overall CAC while driving scale
• Perform ad hoc data requests
• Deliver on ambiguous projects with multiple stakeholders, unclear requirements and incomplete data

What we can offer:

• Full Medical, Vision and Dental coverage
• Dependant coverage available
• FSA, HSA plus fitness reimbursements.
• Basic life and AD&D is provided
• Commuter benefits
• Flexible PTO policy
• Fun, collaborative and ambitious environment

Mynd is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status.