AI Implementation Analyst (Construction Management) - Gryps
At a glance
Mid-level Solutions & Sales Engineering role at Pear VC. New York · full-time · $100,000–$150,000 base.
Growth Roles summary, based on the employer's posting.
What you'll do
- Learn how customers make decisions and find data that can improve those choices
- Examine construction-system and public datasets to understand their structure and usefulness
- Configure dashboards, reshape business processes, and lead whiteboard sessions about data use
- Build descriptive, predictive, and prescriptive analyses with Python and Jupyter Notebook
- Advise customers on Gryps data use while documenting workflows, policies, standards, and procedures
What you bring
- A quantitative undergraduate or master’s degree, or a construction management degree
- At least two years analyzing quantitative data and solving complex problems in construction
- At least two years of experience in the construction industry
- Working knowledge of SQL and Python plus a visualization or exploration tool such as Quicksight, Power BI, Tableau, or Jupyter Notebook
- Strong communication skills and a customer-oriented approach to data-driven decisions
Who this fits
You’ll suit a customer-facing role that combines construction knowledge, data analysis, AI applications, and process innovation. You’ll work directly with the CEO and customers, collaborate across teams, and help shape data strategy and product direction. The role is onsite in New York and fits someone seeking a mid-level position on a small team.
From the employer
We are a product-focused organization that dreams big and achieves those dreams. Our customers are large players in the construction industry. This is an opportunity to be part of a nimble team where every individual becomes an expert in their area. We work fast, iterate quickly, and create a product that transforms how our customers work through AI.
This is the place for you if you’ve worked in a role at the intersection of AI, automation, data analytics, construction tech, construction management, and innovative technology—and you’re looking for the next leap in your career.
We’re a growing company backed by Primary Ventures, LDV Capital, Pear VC, and other top investors. You will work directly with the CEO and our customers—large organizations that own and operate hospitals, universities, and public infrastructure. You’ll have the opportunity to shape our data strategy by exploring various data sources and datasets, running exploratory AI models, and providing analytics that support customer decisions. This is a unique chance to join early and shape your career with Gryps.
Must Haves
Have an undergraduate or Master’s degree in a quantitative field (e.g., mathematics, engineering, statistics, or similar) or construction management
2+ years of work experience involving quantitative data analysis and complex problem-solving in construction
Proficiency in SQL and Python, along with experience using Quicksight, Power BI, Tableau, Jupyter Notebook, or other data visualization and exploration tools
Have 2+ years of construction industry experience
Possess excellent interpersonal and communication skills
Are curious, a great listener, and enjoy working with customers to find data-driven ways to support decision-making
You would love your job if you:
Are customer-obsessed and love helping people apply AI in their workflows
Are looking to join a small team and grow with it
Get excited by creating new processes, working with data, and innovating data applications
Are intrigued by how AI and RPA will change the construction industry
Love collaborating across teams to solve problems
Want to grow your career in customer success, data analytics, data science, or machine learning
Are passionate about disrupting the construction industry with technology
Are a fast learner or have a deep understanding of technology systems in the construction industry
Love working with data to uncover patterns and insights
What you'll be doing:
Understanding customer decision-making and identifying data that can influence those decisions
Analyzing data structures from construction systems or public data sources
Setting up customer dashboards, reconfiguring business processes, or leading whiteboard sessions to map out customer data use
Identifying and proposing potential data sources that could support customer decision-making
Consulting with customers on how to leverage their data via the Gryps platform
Documenting data workflows, data policies, structures, standards, and procedures for customer systems
Developing and running advanced descriptive, predictive, and prescriptive analytics using Jupyter Notebook and Python
Gathering feedback on current Gryps use cases and identifying new opportunities
We recognize you as an early joiner by:
Competitive compensation
Flexible paid time off
Medical, dental, and vision benefits
Flexible career path
Direct influence on our product and company roadmap
About the Company
Gryps is a NYC-based, VC-backed startup on a mission to revolutionize the $10T construction industry by transforming the way capital projects are managed by owners and operators of construction programs.
Our Robotic Process Automation and AI platform sets Gryps apart by automatically ingesting, understanding, augmenting construction data and automating workflows—delivering actionable insights and more efficient workflows through intelligent applications. Our products have already transformed operations for top owners and developers in the US by streamlining construction processes.
At Gryps, we foster a culture of innovation, where brilliant minds collaborate to solve complex challenges. Our diverse team of talented engineers and industry experts drives our continuous pursuit of excellence.
With an ambitious product roadmap and fresh funding to fuel our growth, Gryps is poised to transform the construction industry. To achieve this vision, we are seeking exceptional professionals to join our dynamic team and help bring our revolutionary ideas to life.
Join Gryps today and be a part of reshaping a $10T industry!
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