At a Glance
- Tasks: As a Data Scientist, you'll analyze data to drive insights for marketing, sales, and product teams.
- Company: Pacaso makes second home ownership easy and enjoyable, backed by former Zillow executives.
- Benefits: Enjoy competitive salary, stock options, excellent insurance, and generous home office stipends.
- Why this job: Join a certified Great Place to Work with a culture recognized as one of the best in real estate.
- Qualifications: 5+ years of analytical experience, strong SQL skills, and knowledge of Python or R required.
- Other info: Remote work opportunity with quarterly team-building events and a focus on diversity and inclusion.
The predicted salary is between 78000 - 108000 £ per year.
About Pacaso:
Pacaso exists to enrich lives by making second home ownership possible and enjoyable for more people. Our innovative co-ownership model is the easiest, smartest and most responsible way for people to experience the joy of a second home. We provide all the benefits of true ownership without the hassles through our simplified financial structure, easy and equitable scheduling, and dedicated local property management. Founded by former Zillow executives, Pacaso has facilitated over $1 billion in gross real estate transactions and service fees across more than 40 markets nationwide, as well as internationally in Paris, London, and Cabo.
We have been featured in The New York Times, Wall Street Journal, Fortune, Forbes, CNBC and more. Pacaso is a certified Great Place to Work and has received numerous accolades for its workplace culture. Fortune and Great Place To Work named Pacaso to the 2024 Best Workplaces in Real Estate list. In 2023, Pacaso was recognized as a Best Workplace in the Bay Area, and in 2022, it ranked among the Best Medium Workplaces, Best Workplaces for Real Estate, and Best Workplaces for Millennials. Additionally, Pacaso was ranked #6 on Glassdoor’s 2022 list of Best Places to Work and was one of LinkedIn’s top startups in 2022.
About the Role
As a Data Scientist you will be an early crew member at a growth-stage company led by some of the most seasoned and successful leaders in the real estate and travel space. This position will support Advanced Analytics initiatives across the Pacaso enterprise. Reporting to the Chief Technical Officer you will play a pivotal role in bringing critical customer insights to multiple stakeholders across Pacaso including Marketing, Sales and Product teams. This role will be part of a multi-functional agile team responsible for using predictive and descriptive analytics to forecast consumer demand, enhance decision making and drive actions towards Pacaso’s strategic priorities.
What you will do
- Identify and apply appropriate methods to acquire, explore, cleanse, and fuse data from different sources.
- Define and operationalize the detailed tracking of company-wide, team-specific, and product-specific performance metrics via dashboards, and automated reporting.
- Efficiently communicate analyses and recommendations to cross functional stakeholders for decision making.
- Support the adoption of analytic products through effective storytelling and collaboration with key partners.
- Designing and analyzing experiments to measure the impact of new product features.
- Building models to predict the growth trajectory of different customer segments.
- Effectively document new business intelligence tools and processes, as well as maintain documentation for existing tools as development changes over time.
Skills/ Qualifications
- 5+ years experience developing analytical insights across teams.
- Strong SQL querying skills and database skills.
- Knowledge of at least one modern scripting language (preferably Python or R).
- Expert knowledge of data visualization tools and techniques (Tableau, Looker, Power BI, D3).
- Experience with cloud data technologies and tools (AWS preferred).
- Understanding of ML algorithms (SVM’s, gradient boosted decision trees, deep neural networks, etc.).
- Experience with consumer engagement modeling, funnel optimizations etc. preferred.
Compensation
- Range around $153k with equity.
You’ll love working at Pacaso because of our …
- Competitive salary and stock options.
- Excellent medical, dental and vision insurance.
- Sponsored memberships to One Medical, Ginger and Carrot.
- 401(k) to help you save for the future.
- Paid maternity and paternity leave.
- Generous home office stipend and monthly cell phone reimbursement.
- Quarterly remote team building events and L&D opportunities.
Pacaso encourages applications from people of all races, religions, national origins, genders, sexual orientations, gender identities, gender expressions and ages, as well as veterans and individuals with disabilities.
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Data Scientist United States, Remote employer: Tbwa Chiat/Day Inc
Contact Detail:
Tbwa Chiat/Day Inc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist United States, Remote
✨Tip Number 1
Familiarize yourself with Pacaso's innovative co-ownership model and how it differentiates itself in the real estate market. Understanding their unique approach will help you align your insights and analyses with their strategic priorities.
✨Tip Number 2
Brush up on your SQL and data visualization skills, especially with tools like Tableau or Power BI. Being able to showcase your ability to create insightful dashboards will be crucial in demonstrating your fit for the role.
✨Tip Number 3
Prepare to discuss your experience with predictive analytics and machine learning algorithms. Highlight specific projects where you've successfully applied these techniques to drive business decisions, as this will resonate well with the team at Pacaso.
✨Tip Number 4
Showcase your storytelling abilities when it comes to data. Be ready to explain how you've effectively communicated complex analyses to non-technical stakeholders in the past, as collaboration is key in this role.
We think you need these skills to ace Data Scientist United States, Remote
Some tips for your application 🫡
Understand the Company: Before applying, take some time to understand Pacaso's mission and values. Familiarize yourself with their innovative co-ownership model and how it enriches lives. This knowledge will help you tailor your application to align with their goals.
Highlight Relevant Experience: In your resume and cover letter, emphasize your 5+ years of experience in developing analytical insights. Be specific about your skills in SQL, data visualization tools, and any relevant projects that showcase your ability to drive decision-making through data.
Showcase Technical Skills: Make sure to detail your proficiency in modern scripting languages like Python or R, as well as your experience with cloud data technologies. Providing examples of how you've used these skills in past roles can strengthen your application.
Craft a Compelling Cover Letter: Use your cover letter to tell a story about your passion for data science and how it can contribute to Pacaso's strategic priorities. Discuss your approach to problem-solving and how you can support cross-functional teams with your analytical insights.
How to prepare for a job interview at Tbwa Chiat/Day Inc
✨Showcase Your Analytical Skills
Be prepared to discuss specific projects where you've applied your analytical skills. Highlight your experience with SQL, Python, or R, and how you've used these tools to derive insights from data.
✨Understand the Company’s Mission
Familiarize yourself with Pacaso's co-ownership model and its impact on second home ownership. Being able to articulate how your role as a Data Scientist can contribute to this mission will impress the interviewers.
✨Prepare for Technical Questions
Expect questions related to data visualization tools and machine learning algorithms. Brush up on your knowledge of Tableau, Looker, and AWS, and be ready to explain how you've utilized these technologies in past roles.
✨Communicate Effectively
Since the role involves collaborating with cross-functional teams, practice explaining complex data insights in simple terms. Use storytelling techniques to convey how your analyses can drive decision-making and support strategic priorities.