Remote Life Sciences Solutions Engineer

Domino Data Lab; Town of Montana (WI); On-site; USD 110,000 - 170,000; Full time

Job summary

Domino Data Lab seeks a Solutions Engineer to engage with life-sciences customers, design and run PoCs, and shape deployment strategies that move models toward production. You’ll work with account executives to address governance, reproducibility, and validation needs, and you will build reusable platforms to accelerate future engagements.

You will leverage Python and R, contribute to internal platforms, and help customers realize the value of Domino’s dataset and experiment tracking

Qualifications

• Technical background in life sciences or tech, with experience translating user needs into technical solutions.
• Proven ability to build and explain end-to-end data science workflows for non-technical stakeholders.
• Experience in solutions engineering, pre-sales, or customer-facing technical roles.

Responsibilities

• Engage with customers to understand workflows and constraints before proposing solutions.
• Design and run hands-on proof-of-concept projects in customers' environments.
• Collaborate with account executives to craft architectures addressing life sciences requirements.
• Identify novel use cases and surface opportunities beyond initial engagement scope.
• Build reusable technical environments to accelerate future engagements.
• Partner with Customer Success to ensure successful production deployments.

Skills

Python

R

Solutions engineering

Pre-sales

Life sciences domain knowledge

Education

Bachelor's in Life Sciences or Computer Science

Tools

Python tooling

Data science tools

Job description

Domino Data Lab seeks a Solutions Engineer to engage with life-sciences customers, design and run PoCs, and shape deployment strategies that move models toward production. You’ll work with account executives to address governance, reproducibility, and validation needs, and you will build reusable platforms to accelerate future engagements.

You will leverage Python and R, contribute to internal platforms, and help customers realize the value of Domino’s dataset and experiment tracking