Sr. Bioscience Account Manager – Field Sales
Thermo Fisher ScientificSalary not specified
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Pharmaceuticals, Biotechnology, Life SciencesIndustries
Requirements
- PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in discovery, preclinical, CMC, and/or Quality
- Extensive hands-on experience or direct oversight in one or more of the following areas: high throughput screening, preclinical toxicology, materials engineering, analytical development, drug substance (DS) synthesis and manufacturing
- Delivered requirements for AI/ML-driven solutions in operational or productized environments that improved efficiency, reduced cost, and enhanced data utilization
- Extensive hands-on experience with scientific data workflows and lab automation; exposure to FAIR principles and modern data architecture is a plus
- Strong coding or scripting background (e.g., Python, Nextflow, AWS, SDKs) and familiarity with scientific tools, databases, and ontologies is preferred
- Exceptional communication and storytelling ability to engage technical and executive stakeholders
- Prior experience in customer-facing, consulting, or commercial-scientific interface roles
- Strategic, analytically minded professional with passion for bridging scientific insights and cutting-edge technology
- Ability to collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes
- Skilled at uncovering innovative use cases that drive AI and machine learning applications
- High clock speed and forward-thinking individual with passion for developing requirements for complex solutions targeted to R&D and Quality personas in Life Sciences
- Embodies extreme ownership and demonstrated history of deriving maximum value from data through enrichment, analysis, and integration with AI and machine learning applications
- Energized by regularly working onsite with customers and thriving in dynamic, high-impact, face-to-face collaborative environments
Responsibilities
- Collaborate with scientists, product managers, and engineers to transform complex scientific data into actionable outcomes
- Uncover innovative use cases that drive AI and machine learning applications in drug discovery/preclinical development, CMC, or Quality
- Develop requirements for complex solutions targeted to R&D and Quality personas inside of Life Sciences
- Engage with scientists and business leaders to maximize the value of scientific data
- Work onsite with customers to build deep relationships and drive scientific transformation firsthand
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What is the salary for this Scientific Business Analyst position?
This information is not specified in the job description.
Is this role remote or on-site?
The position is on-site, and candidates should be energized by regularly working onsite with customers in dynamic, face-to-face collaborative environments.
What qualifications and skills are required for this role?
Candidates need a PhD with 15+ years of industry experience in life sciences, preferably across pharma, biotech, or health tech, with deep domain expertise in drug discovery/preclinical development, CMC, or Quality. They must be strategic, analytically minded, high clock-speed, forward-thinking, with a passion for bridging scientific insights and technology, developing requirements for complex solutions targeted to R&D and Quality personas in Life Sciences, and deriving value from data through AI and machine learning.
What is the company culture like at TetraScience?
TetraScience emphasizes a unique values and ethos outlined in 'The Tetra Way' letter by the CEO, which candidates must review and embody if joining. The culture values alignment with their approach to company and team building, extreme ownership, high clock-speed collaboration, and thriving in dynamic, high-impact environments.
What makes a strong candidate for this position?
A strong candidate has a PhD with 15+ years in life sciences, deep expertise in drug discovery, preclinical, CMC, or Quality, and thrives bridging science and AI technology while working onsite with customers to develop requirements and drive data value.
TetraScience
Cloud platform for scientific data management
About TetraScience
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.
Boston, MassachusettsHeadquarters
2019Year Founded
$113.8MTotal Funding
SERIES_BCompany Stage
AI & Machine Learning, Biotechnology, HealthcareIndustries
51-200Employees
Benefits
Unlimited PTO
100% company paid health, dental, & vision
Company paid life insurance
401k savings
Company paid disability insurance
Equity program
Flexible work arrangements
Risks
Rapid AI development may outpace TetraScience's integration capabilities, risking obsolescence.
Dependency on partners like Google Cloud and NVIDIA could pose risks if disrupted.
International expansion may expose TetraScience to regulatory and compliance challenges.
Differentiation
TetraScience offers a vendor-neutral, open, cloud-native platform for scientific data management.
The platform integrates with any lab equipment or software, enhancing flexibility and adaptability.
TetraScience's Scientific Data Cloud centralizes and harmonizes data, preparing it for AI/ML applications.
Upsides
Partnerships with NVIDIA and Google Cloud enhance AI-native scientific datasets and capabilities.
Collaboration with Databricks accelerates the Scientific AI revolution in life sciences.
Bayer AG partnership maximizes scientific data value, driving innovation in biopharma.
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