Data Scientist- Solution Architect | Opmed.ai · Teeming.ai
Opmed.ai
Supercharge Your OR Schedule and Management -
Unlock your OR's full potential, ensure optimal resource utilization and build resilience with the power of AI and Network Science.
Supercharge Your OR Schedule and Management -
Unlock your OR's full potential, ensure optimal resource utilization and build resilience with the power of AI and Network Science.
Headquarters: Boston, Massachusetts, United States
Product: AI-driven platform for operating room and perioperative scheduling, resource optimization, and analytics
Recent funding: $15M Series A (May 2024)
Founders: Dr. Mor Brokman Meltzer (CEO), Avi Paz (CTO), Prof. Baruch Barzel (Chief Scientist)
Company Overview
Problem Domain
Healthcare operations optimization focused on operating room and perioperative/procedural scheduling and resource planning.
Industry
Software Development
Funding Track Record
Series A- May 2024
$15M
Round included participation from Secret Chord Ventures, Sir Ronald Cohen, and Unbox Ventures.
Investor Signal
“Led by prominent early-stage investor NFX with participation from VC firms and angel/backer Sir Ronald Cohen”
Founders
What we do
Join the Team
Data Scientist- Solution Architect
RemoteUS
Remote • US
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About Opmed.ai
Opmed.ai is a rapidly growing healthcare AI startup helping leading health systems optimize their operations. Our platform is already in use at major health systems and large networks such as Mayo Clinic and Geisinger, and we are backed by world-class funds including NFX and Grove.
Our platform improves patient access, staff satisfaction, and financial performance by transforming complex planning, scheduling, and resource allocation decisions (including equipment and staff) into data-driven workflows.
This is an opportunity to join a company in a phase of significant growth, working with leading health systems and a strong multidisciplinary team.
Role Overview
We are looking for a hybrid Data Scientist – Solution Architect who will sit at the intersection of data, product, and go-to-market. This person will own the technical win in pre-sales: analyzing customer data and constraints, designing models for planning, scheduling, and valuation, and building clear, quantitative business cases that demonstrate the impact of Opmed.ai.
You will work closely with sales, customer success, product, and R&D, and you will regularly interact with operational and executive leaders at leading health systems.
Key Responsibilities
Requirements
3+ years of experience in Data Science, Operations Research, Applied Analytics, or a similar quantitative role.
Strong hands-on skills with:
• Python
• SQL and working with relational data.
Experience with statistical modeling and/or optimization for scheduling, planning, resource allocation, or similar problems.
Ability to build quick, pragmatic models and analyses that answer business questions, not just “perfect” research models.
Background in optimization (constraint programming, mixed-integer programming, scheduling, routing).
Previous experience in a Solution Architect / Sales Engineer / Pre-sales Data Scientist type role.
Experience in B2B SaaS, especially with enterprise customers.
Experience working with US health systems and their data (EHRs, scheduling systems, etc.).
What This Role Offers
Direct impact on strategic deals with leading health systems worldwide.
The opportunity to shape how Opmed.ai runs pre-sales and proof-of-value projects.
Close collaboration with a strong R&D team building state-of-the-art AI and optimization solutions.
A front-row seat to how data and models translate into real-world improvement in healthcare operations.
An opportunity to join a company in significant growth, with room to influence both technology and business outcomes.
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Partner with sales to lead technical discovery and pre-sales projects with prospects and customers.
Perform data assessments: understand available data sources, data quality, and constraints relevant to planning, scheduling, and capacity/resource management (including equipment and staff).
Translate operational workflows (OR, radiology, rehab, etc.) into models for:
Case length and volume forecasting
Planning, scheduling, and assignment (rooms, staff, equipment, blocks)
Valuation and ROI estimation for different scenarios.
Build prototypes and proof-of-value analyses using real customer data in Python.
Quantify impact (access, utilization, overtime, revenue, waiting time) and translate it into a clear business case.
Present findings and recommendations to customer stakeholders (operational and executive) in a clear and structured way.
Work closely with R&D and product on scoping, assumptions, and handover from pre-sales projects to implementation.
Collaborate with the R&D team, who will perform code reviews and validate the technical quality and robustness of your work.
Develop reusable playbooks, templates, and best practices for future pre-sales engagements.
Represent Opmed.ai as a technical expert in customer calls, workshops, and demos.
Experience working directly with customers or stakeholders (client-facing, consulting, pre-sales, or internal business partners).
Excellent communication skills, including the ability to explain complex models and tradeoffs to non-technical audiences.
Comfortable presenting to senior stakeholders (directors, VPs, C-level).
The position requires up to 25% travel based on business needs
