Job Location: Remote
Job Detail:
Are you looking for an exciting career with a growing team in a recession-resistant industry focused on collaborative teamwork? Come join the team!
Headquartered in San Francisco’s trendy South Beach, and operating in 6 states, Baco Properties is looking for a remote Data Scientist to join our Data & Analytics Pricing team.
The Data Scientist will use our pricing team’s business domain and technical skills to optimize revenue through new customer rates, web discounts, and existing customer management. Additional duties may include working with the Marketing and digital team to help analyze the spending on Google, Yelp, and other platforms to maximize the return rate. The position may also assist in property acquisition and market analysis for potential new or expanded locations. The ideal candidate works with multiple departments and regions to provide pricing and market intelligence on storage unit rental performance, existing tenant length of stay, and average spending. The position provides Regional Managers, Senior Leadership, and Ownership with the information required to establish and measure category pricing strategies, tactics, and rules.
Key Responsibilities and Accountabilities:
- Track and test multiple variables around discounting, rate changes, and length of stay to maximize sales and profit.
- Research, synthesize, and interprets data/information from various internal and external sources to assess impact analysis on current events and predict the future business impact on the company.
- Use various statistical modeling methods to prepare reports showing the potential impact of different pricing strategies. These models allow us to set targets for forecasted revenue, discounts, space rentals & occupancy.
- Monitor and test market trends within the industry for potential improvement in sales and profitability.
- Develop pricing tools that quickly respond to changing market needs and trends.
- Maximize revenue generation through data gathering and analytic techniques and analysis.
- Provide Category pricing analysis (Units, Sales, Cost, Forecasting & Remaining Market opportunities).
- Develop models comparing multiple properties in crucial demographics to test how pricing changes impact consumer spend, occupancy, and length of stay.
Requirements (Knowledge, Skills, and Abilities)
- Strong communication (written and verbal) skills.
- Ability to communicate and interact effectively and appropriately with a broad audience.
- Knowledge and usage of applicable computer systems
- Knowledge and use of Price Optimization software
- Knowledge and use of market data platforms
- Ability to work independently and within a team.
Experience with one or more of the following tools/programs/languages is a plus.
· SQL, Python, and Excel proficient
· Domo, Tableau, Google Analytics, Google AdWords, Google Big Query
· Scheduling/Query tools such as SQL Server Management Studio
Education: Four-year degree or equivalent knowledge gained through formal education, specialized training, or additional job experience. Sufficient job experience may be considered in place of a degree.
Experience: Three to five years of related experience in pricing, data modeling, and analyst roles
Physical: Basic office environment: the ability to sit, stand, walk, kneel, stoop, use stairs, reach, pull and lift objects
Benefits:
- 401(k) matching
- Dental Insurance
- Employee assistance program
- Employee discount
- Flexible spending account
- Health insurance
- Health savings account
- Paid time off
- Parental leave
- Referral program
- Vision insurance
Job Type: Full-time
Pay: $125,000.00 – $135,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible spending account
- Health insurance
- Health savings account
- Paid time off
- Parental leave
- Referral program
- Vision insurance
Schedule:
- 8 hour shift
- Day shift
- No nights
- Overtime
- Weekend availability
Education:
- Bachelor’s (Preferred)
Experience:
- Data science: 3 years (Preferred)
Work Location: Remote
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