Proteins are the molecular machines of life, used for many therapeutic, diagnostic, chemical, agricultural and food applications. Designing and optimizing proteins currently takes a lot of expert knowledge and manual effort, through the use of custom computational and biological tools. However over the past few years, machine learning has completely changed this story: we can now build high-fidelity models of proteins in computers.
At Cradle, we build these models. We offer a software platform for AI-guided lead optimization of proteins, so that biologists can design proteins faster and at scale. We’re already used by clients across pharma, biotech, agritech, foodtech, and academia.
We're an experienced team, now of just over 40 people. We've built many successful products before and have enough funding for multiple years of runway. Our technical roles are split between machine learning, our web platform, infrastructure & scaling, and wet lab.
We're focused on building the best possible team culture. We're distributed across two locations, and are flexible about when and where we work.
We offer our employees a top of the market salary, a generous equity stake in the company and a wide range of benefits from health and wellbeing, financial, to training and career progression opportunities.
Context
As Account Executive at Cradle, you will join a small but mighty commercial team and help to scale a fast-growing startup. You will join at an exciting time at a startup that found product market fit and is ready to scale, with the ambition to help biologists across the world to develop better protein-based products using advanced Machine Learning tools.
You’ll drive business development; nurture leads, identify opportunities and close deals with world-leading biotech and biopharma organizations to bring in millions of annually recurring revenue. The feedback and strategic insights that you gather from speaking directly to prospective customers will help to steer our roadmap.
You’ll work closely alongside Cradle’s product, engineering, and customer success teams to craft proposals for top accounts. You’ll network with scientists and executives in global biotech and biopharma, attend events across the world, and become well-known in this space. In a team that is thinking big and expanding rapidly, there are few limits to this role.
Responsibilities
Develop and manage our sales pipeline, close deals, and contribute to expanding our potential customer base.
Bring new prospects into the pipeline.
Collaborate with colleagues from the Machine Learning team to scope projects and ensure technical fit.
Navigate sales cycles with players ranging from startups to mid-market and enterprise players, securing six to seven figure deals.
Own improvements to the existing sales process. You will spot opportunities for improvement and contribute to upgrading anything from our CRM workflows to sales materials, communication and outbounding strategies.
Cultivate relationships with everyone from scientists to C-level, gaining an understanding of their needs and decision making process.
Need to haves
Advanced degree in the life sciences (structural or molecular biology, bioinformatics, pharmaceutical sciences, biochemical engineering, or other) OR multiple years of work experience interacting with life sciences R&D.
3+ years of experience in an (enterprise SaaS) B2B sales role, or similar.
Proven track record of consistently exceeding sales quota (top 5%).
You are a team player who thrives in a fast-paced and ambiguous environment, not afraid to write the required playbooks yourself.
You listen intently, are innately curious, and learn with humility.
Exceptional analytical skills. Cradle is building a complex product at the interface of protein engineering and machine learning. This does not intimidate you, as you have previously shown to rapidly understand and articulate complex technical concepts, and translate them into industry- or business-relevant terms.
Nice to haves
Strong business network in global biotech and pharma.
Domain knowledge of machine learning.
Prior experience at a (B2B) growth-stage startup.
Prior experience working as bioinformatician or wet lab scientist in an industrial or academic setting.
Application deadline
We are reviewing applicants on a rolling basis.
Did we pique your interest? We'd love to hear from you. Please use this form to apply directly.
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