Pre Sales, Data Science FAS Manager

Reposted 20 Days Ago
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New York, NY, USA
In-Office
165K-228K Annually
Mid level
Artificial Intelligence • Biotech
The Role
As a Pre-Sales, Data Science FAS Manager, you'll support sales by demonstrating the platform, addressing customer questions on analytics, and collaborating with Product and Data Science teams.
Summary Generated by Built In

About QuantHealth
QuantHealth (QH) is a rapidly growing company specializing in the development of a cutting-edge platform for simulating clinical trials using big clinical data and state-of-the-art AI technologies. Our mission is to provide innovative solutions to pharmaceutical and biotechnology companies for de-risking the drug and clinical development process. 
We are looking for a Pre-Sales individual contributor with strong expertise in both medical and data sciences to join our team, to support the company’s commercial efforts, working directly with pharma and biotech clients to help drive impactful collaborations. 

The Role
As a Pre-Sales, Data Science FAS Manager, you will serve as a technical and scientific ambassador for QuantHealth’s platform. You will work within Sales, and in tight collaboration with Product, and Data Science teams to articulate the value of our models, demonstrate our technology to prospects and customers, and support commercial engagements with deep technical credibility.
The annual salary for this role is $165,000 - $228,000, depending on experience, skills, and other relevant considerations. 

Responsibilities

  • Act as a technical partner to Sales, supporting pre-sales and post-sales engagements 
  • Lead platform demonstrations and technical walkthroughs 
  • Explain and defend KG and RWD-driven models 
  • Answer in-depth customer questions on data sources, modeling, and validation 
  • Translate complex analytics into commercially relevant narratives 
  • Collaborate with Product and Data Science teams 
  • Provide customer feedback to inform roadmap and messaging 

Qualifications 

  • Advanced degree (MS or PhD preferred) in a quantitative field 
  • Deep hands-on data science experience (experience at consulting or pharma company highly preferred) 
  • Experience with machine learning, statistical modeling, and real-world data 
  • Commercially minded and customer-facing 
  • Strong communication and presentation skills 
  • Strong Preference for: biostatistician or epidemiologist with 3-7 yrs in pharma/biotech (sponsor-side or CRO), deep understanding of clinical trial design, endpoints, and regulatory submissions 

Who You Are 

  • A hybrid thinker who enjoys both deep technical problem-solving and customer interaction 
  • Comfortable leading scientific discussions with senior stakeholders 
  • Naturally curious, pragmatic, and impact-driven 
  • Confident explaining complex models without oversimplifying 
  • Energized by supporting revenue-generating conversations 

What Success Looks Like in 30 Days 

  • Confidently delivering end-to-end platform demos independently 
  • Supporting live sales cycles with minimal ramp support 
  • Clearly articulating QuantHealth’s modeling approach and value proposition 
  • Building trust with Sales, Product, and Data Science teams 
  • Contributing actionable feedback from customer conversations 


Top Skills

AI
Machine Learning
Statistical Modeling
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The Company
Tel Aviv
36 Employees
Year Founded: 2020

What We Do

QuantHealth is an AI company conducting patient-centric drug simulations to accelerate and de-risk drug development. Over 90% of drugs in clinical development stage fail to reach the market, which accumulates to a $45B/year direct lost to the pharma and biotech industry. Our platform allows our pharma and biotech partners to rapidly run thousands of variations of their clinical trials to optimize the trial design and significantly increase the probability of trial success, all while enabling discovery of new clinical opportunities and optimization strategies. QuantHealth has one the largest integrated datasets that spans the clinical, pharmacological and biological domains together with a proprietary AI platform that can predict patient-response to both approved and novel therapies.

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