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workfully
workfully

Senior Solution Data Scientist

Location

Remote restrictions apply
See all remote locations

Salary Estimate

N/AIconOpenNewWindows

Seniority

Senior

Tech stacks

Data Science
Data
Project management
+18

Permanent role
11 days ago
Apply now

Company: Confidential

Why candidates should join

This is a high-impact role at the intersection of data science, biology, and customer success. You’ll work directly with leading biopharmaceutical companies on scientifically meaningful problems while helping shape a high-quality SaaS platform.

You’ll have the chance to influence both customer outcomes and the future product roadmap by translating real-world modeling challenges into new capabilities, workflows, and solutions.

Role Requirements

  • Lead-level ownership of customer projects (Must-have)
  • Strong background in data science, applied mathematics, or computational biology (Must-have)
  • Python and data science/ML libraries (Must-have)
  • Mechanistic modeling concepts (Must-have)
  • Hybrid modeling approaches (Must-have)
  • Model validation (Must-have)
  • Data visualization and presentation (Must-have)
  • Bioprocess or omics data experience (Nice-to-have)
  • Cloud environments such as Azure, AWS, or GCP (Nice-to-have)
  • Outstanding communication with scientific and non-technical audiences (Must-have)
  • Strong ownership and independence in customer-facing projects (Must-have)
  • Scientific curiosity and proactive mindset (Must-have)
  • Ability to translate customer needs into internal requirements (Must-have)
  • Cross-functional collaboration in a remote environment (Must-have)

About The Role

Lead customer modeling projects end-to-end for a biopharmaceutical software platform that combines AI, mechanistic modeling, and bioprocess expertise. The role spans data intake and preprocessing, building and validating hybrid models, communicating results, and helping customers move from fully managed modeling toward self-sufficient use of the platform.

You will be the technical interface between customers, modeling workflows, and product teams. Success means delivering scientifically sound insights, improving customer adoption and time-to-first-value, and turning real customer needs into product and modeling requirements.

Interview process

  • Shortlisted
  • Screening
  • Recording review
  • 1st stage
  • Offer sent

About workfully

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