About RentSpree
RentSpree, the USA's leading home rental software, is among the fastest-growing property tech startups. Our award-winning software connects renters and landlords, revolutionizing the residential rental industry. With six years of annual growth, we've forged partnerships with 300+ top real estate companies, delivering high-quality data-driven insights and products
RentSpree is a place where you will grow alongside the company while collaborating within your team to have a meaningful impact on RentSpree’s future.
The Opportunity
Join the Data Analytics team at RentSpree as a Staff Data Analyst! You will play a crucial part in collaborating with our Product team, offering advanced analytics and innovative data solutions to address our users' pain points. This position offers a unique opportunity to work collaboratively with cross-functional teams located in Thailand and the US, driving innovation in the real estate market.
If you're ready to tackle exciting projects that harness the power of our massive data stores, and you're passionate about building solid data products, then we want you! Take the lead and bring your self-directed skills to RentSpree.
Key Responsibilities
- Partner closely with the product team to develop and implement tools and processes to analyze product funnels, optimize user experience and craft data-driven product strategic decisions
- Evaluate product efficiency by monitoring key metrics for continuous optimization
- Design and conduct A/B tests and experiments to assess the impact of products changes on user behavior and product performance
- Collaborate with other departments and teams to ensure that data analysis is integrated into all aspects of the company's operations
- Create innovative data solutions using AI to address product challenges, automate and streamline processes, predict user behavior, and enhance overall product performance
- Stay informed about industry best practices and trends related to data science, and apply this knowledge to enhance company-wide practices
- Mentor and coach team members to build their data skills and knowledge
- Provide trainings on advanced analytics methods and machine learning, fostering a collaborative environment focused on leveraging data for product innovation
Skills & Requirements
- Bachelor's or Master's degree in a relevant field such as Analytics, Data Science, Statistics, Computer Science, etc
- Minimum of 6 years of experience in data science or analytics role, preferably in a similar industry
- Strong understanding of data analysis methodologies, statistical analysis, data visualization, and data modeling
- Strong understanding of the company's business objectives and how data can support those objectives
- Proficiency in tools such as SQL, Python, R, Excel, Tableau, and other business intelligence tools
- Experience with BI tools, such as Holistics, Looker, PowerBI, Data Studio, or Tableau or similar
- Have a growth mindset, be open to new experiences, and be at ease with sharing your expertise with others
- Experience in fostering a data-driven culture within an organization is highly valued
- Experience in real estate business is a plus
Skills & Requirements Benefits & Perks
- Performance Rewards
- Unlimited Annual Leave
- Provident Fund
- Group Health insurances
- Flexible Benefits
- Workstation Benefits
- Lunch & Learn Allowance
- Internet Allowance
- Team Training & Event Budget
- Weekly Office Massage Service
More about us!
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EEO Statement:
RentSpree is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.
This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. RentSpree makes hiring decisions based solely on qualifications, merit, and business needs at the time.