…If I could spearhead a global initiative, I would launch an open-source platform designed to democratize access to advanced analytics and AI, particularly for non-profits, social enterprises, and organizations in emerging markets. There remains vast, untapped potential to use decision science to address critical challenges in healthcare, education, and disaster response. By lowering technical and financial barriers, such a platform could empower mission-driven organizations to leverage state-of-the-art analytics and machine learning for societal good. My vision is to enable global talent, foster collaboration across borders, and ensure that transformative technologies are accessible to those who can make the greatest impact…
In today’s fast-evolving tech landscape, artificial intelligence is transforming industries at an unprecedented pace. Real estate, once considered a slow adopter, is experiencing its own AI revolution. From streamlining operations to redefining customer experiences, companies like Opendoor are leading the charge. At the heart of this innovation is Paras, the Head of Data and Decision Science at Opendoor, who is steering the integration of data, machine learning, and AI to drive business growth.
With over 12 years of experience across tech giants like Amazon and other innovative firms, Paras Doshi has built a career on leveraging data to unlock profitability and scale. At Opendoor, he leads a 30-person team tasked with managing the data backbone that powers algorithmic home buying and selling. In this interview, Paras shares his insights on leadership, the challenges of managing data in real estate, and how AI is reshaping both his role and the broader business landscape.
Let’s start with your backstory. What led you to explore data science and AI in your career?
My path into data science and AI began with a drive to create meaningful change through technology. At Kiva, I modernized analytics systems for global microfinance, witnessing how data could empower communities worldwide. At Thomas Jefferson University, I applied predictive analytics to enhance fundraising in the nonprofit healthcare sector, deepening my
belief in data-driven solutions for complex challenges.
Building on these foundations, I joined Amazon, where I led teams developing scalable analytics and machine learning frameworks that supported innovative, widely adopted products. Now at Opendoor, I direct data science and engineering efforts that integrate AI into core business processes, shaping how technology transforms the real estate industry. Across every chapter, my focus has been on combining technical expertise with strategic leadership to advance the field and deliver tangible impact.
How did analytics and AI help you solve major business challenges?
Advanced analytics and AI have been central to driving transformation and measurable business value throughout my career. At Opendoor, I was brought in to lead the turnaround of the Marketing Science team, which had struggled with underperformance and fragmented decision- making. By consolidating leadership across marketing, engineering, finance, and research, I architected a unified analytics engine that delivered over $150 million in marketing optimization.
A signature accomplishment was the creation of the “Physics of Marketing” model, a novel framework that enabled the company to make market-specific spend decisions with precision even in highly volatile environments. This model alone generated over $1 million in savings while supporting the company’s continued growth. In parallel, I rapidly scaled Opendoor’s Pricing Decision Science team from one to five members in just a quarter. This enabled the delivery of high-impact analytics solutions that earned the trust of senior pricing leadership and accelerated key business initiatives.
At Amazon, my focus was on operational excellence and innovation on scale. The teams I led developed and rolled out self-service BI tools and automated data pipelines that resulted in over $1 million in annual infrastructure savings. More importantly, these solutions enabled the identification of product opportunities valued at over $1 billion, demonstrating the direct link
between advanced analytics and strategic business outcomes.
What was the initial response to advanced analytics and AI within your teams?
Introducing advanced analytics and AI into established organizations often brings initial skepticism, concerns about complexity, disruption of routines, or the impact on existing roles. I have found that successful adoption requires more than technical expertise; it demands vision,
empathy, and inclusive leadership.
At both Opendoor and Amazon, I prioritized creating a culture rooted in transparency and collaboration. I involved team members early in the process, clearly communicating the purpose behind each initiative and inviting feedback. By designing early “quick win” projects and automating repetitive tasks, I was able to demonstrate the immediate value of our solutions, reducing skepticism and building enthusiasm for further change.
This approach transformed initial resistance into a sense of shared ownership and advocacy. Team members who were once cautious became active champions for advanced analytics and AI, eager to leverage new tools and contribute ideas. Emphasizing the “why” behind our work and consistently linking new technology to tangible improvements in daily operations, was key to fostering lasting engagement and embedding a culture of innovation.
In what ways has data science and AI taken your organizations to the next level?
At Opendoor, I unified analytics efforts across multiple teams, creating a coordinated framework that enabled more precise and data-driven marketing decisions. This resulted in the optimization of over $150 million in marketing investments, elevating the company’s ability to compete in a
dynamic market.
A signature achievement was the development of the “Physics of Marketing” model cutting-edge optimization tool that allowed for real-time, market-specific adjustments to marketing strategy. This innovation not only produced significant cost savings but became a core asset for managing risk and driving growth in challenging economic conditions.
Beyond analytics innovation, I led the overhaul of Opendoor’s Analytics Platform, integrating new engineering teams, streamlining operations, and reducing critical incidents by half. This platform transformation accelerated access to high-quality data, empowered business users, and set new standards for operational excellence.
My approach to team building has also been instrumental in scaling impact. By rapidly assembling and mentoring high-performing teams in Pricing, Marketing, and Analytics Engineering, I ensured that advanced analytics and AI were embedded into the organization’s DNA.
At Amazon, my focus on data democratization resulted in a more than 300% increase in self-serve BI adoption, making actionable insights widely accessible and empowering leaders across the company to make informed decisions faster.
Have you received recognition for your analytics and AI leadership?
Yes, my leadership in analytics and AI has been recognized through some of the most selective honors and roles in the field. I am a recipient of the Globee Award for AI (2025) and the Claro Award (2024), both awarded for transformative contributions and innovation in data science at a global level. As a recognized authority, I have served as a judge for highly competitive, internationally renowned competitions, including the Make Ohio Hackathon, the Live AI Hackathon (jointly organized by Harvard and Duke), and the Globee Awards, regularly collaborating with and evaluating the work of leading experts from organizations such as Meta, Google, Microsoft, and Amazon.
Further extending my impact, I founded Insight Extractor, a premier analytics and AI platform. The blog features more than 600 published articles that have reached over 2 million unique visitors and is followed by an engaged global audience of more than 5,000 data professionals. This platform is widely recognized as a go-to resource for analytics leadership and best practices, amplifying my thought leadership and influence across the international data science community.
What advice would you give to leaders hesitant about embracing data science and AI?
For leaders who are hesitant about adopting data science and AI, I recommend a pragmatic yet visionary approach. Begin with targeted, high-impact projects that offer clear business value but manageable risk. Rigorously measure outcomes, but do not let the pursuit of perfection delay
experimentation, modern open-source tools and agile methodologies enable rapid prototyping and learning.
Involve your teams from the start, encourage cross-functional collaboration, and communicate not just the “how” but the “why” behind each initiative. When people witness firsthand how data and AI can address their real-world challenges, they shift from skepticism to advocacy, fueling a sustainable cycle of innovation.
What trends in analytics and AI excite you the most?
Automated Decision Science: I am energized by the rapid evolution of platforms that integrate advanced analytics and AI directly into decision-making workflows. These systems not only accelerate the pace of business but also elevate the quality of strategic decisions across entire organizations.
Explainable AI: As AI becomes more pervasive, especially in sensitive and regulated sectors, the need for transparency and interpretability has never been greater. Advances in explainable AI are empowering organizations to build trust with stakeholders, ensure compliance, and unlock the full value of intelligent systems.
Global Talent Strategies: The ability to rapidly build and scale diverse, high-impact teams across continents has set new benchmarks for excellence in analytics. Leading the formation of global teams, such as Opendoor’s India Analytics Engineering group, has shown me firsthand how distributed talent and collaboration drive both innovation and resilience in today’s data- driven economy. Together, these trends are not just shaping the evolution of data science and AI, they are expanding the boundaries of what organizations, and our field as a whole, can achieve.
If you could launch a global data or AI initiative, what would it be?
If I could spearhead a global initiative, I would launch an open-source platform designed to democratize access to advanced analytics and AI, particularly for non-profits, social enterprises, and organizations in emerging markets. There remains vast, untapped potential to use decision science to address critical challenges in healthcare, education, and disaster response. By lowering technical and financial barriers, such a platform could empower mission-driven organizations to leverage state-of-the-art analytics and machine learning for societal good. My vision is to enable global talent, foster collaboration across borders, and ensure that transformative technologies are accessible to those who can make the greatest impact.
How can people follow your work?
To connect with my work and insights, I invite you to follow me on LinkedIn and visit insightextractor.com, where I regularly share in-depth articles on analytics, leadership, and best practices in data science and AI. I am deeply committed to mentoring and supporting the next generation of analytics leaders, and I do so through platforms like Springboard. Engaging with the broader data community, whether through thought leadership, mentorship, or collaboration remains central to my mission of advancing our field.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead and advises Authority Magazine’s Thought Leader Incubator.
AI, Data, and Leadership at Scale: Insights from Opendoor’s Paras Doshi was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.