Sales Development Representative, Data

Primary Objective

The Sales Development Representative, Data opens conversations with computational and translational scientists to build pipeline for Champions' data products. Partnering with Data Business Development, Product Development and regional Business Development, this position identifies the questions clients need answered across their development roadmap and brings data-derived insights that strengthen client decisions.

Duties and Responsibilities

• Defines and maintains the ideal customer profile and account tiers with Data Business Development and Marketing.
• Builds target lists of pharma, biotech, and AI-first drug discovery companies, prioritizing lookalikes of existing data customers and accounts with relevant pipeline activity.
• Identifies the right contacts, including computational biologists, bioinformaticians, data scientists, and translational leads, using publications, conference abstracts, professional networks, and sales intelligence tools.
• Engages three buyer groups: pharma and biotech R&D teams de-risking programs; computational and bioinformatics teams seeking clinically annotated, in vivo-linked omics data; and AI-first drug discovery companies seeking training and validation data with patient context.
• Runs personalized, multi-channel outreach (email, LinkedIn, and events) that ties a prospect's programs or published work to a relevant data offering.
• Prepares account-specific data snapshots, short-tailored analyses of Champions data relevant to a target account's programs or indications, and uses them to spark interest and open conversations.
• Responds to inbound interest from the website, campaigns, webinars, and partner data-exchange listings.
• Qualifies conversations on scientific questions, buyer type, data needs (data product, custom project, or partnership; standalone or alongside a preclinical study), timing, and budget, and books discovery calls for the Data team.
• Coordinates with regional Business Development before engaging active accounts, so data outreach supports existing relationships rather than competing with them.
• Maintains accurate CRM records, logs activity, and reports on pipeline generated.
• Reports market feedback, including which buyer personas respond, which offerings resonate, and where exclusivity, pricing, or access questions arise, so positioning keeps improving.
• Helps build the data prospecting playbook by testing messaging, documenting what works, and shaping AI-assisted prospecting workflows.
• Meets activity and qualified-opportunity targets set with management, including ramp milestones over the first six months.
• Occasionally represents Champions at scientific conferences and events; limited travel.
• Works independently and performs other related duties as assigned.

Knowledge, Skills, and Abilities

• Scientific fluency in oncology, genomics, and transcriptomics data, including the ability to read a paper or pipeline entry and identify why it matters.
• Ability to pull together and interpret data analyses and turn them into clear, account-specific snapshots that show a prospect what Champions data could reveal for their work.
• Comfort engaging technical audiences who ignore generic sales outreach.
• Research mindset, with an interest in digging through publications, pipelines, and funding news to find the right account and the right contact.
• Experience with a CRM and disciplined activity tracking.
• Curiosity about AI tools and datasets, and willingness to help build and refine AI-assisted workflows, not just use them.
• Must have the ability to balance several priorities simultaneously with high attention to detail.
• Effective oral and written communication skills in English are required.
• Familiarity with PDX models, preclinical oncology, or translational research workflows is preferred.
• Hands-on exposure to omics data analysis (R, Python, or common bioinformatics tools) is a plus.
• Experience with sales intelligence and prospecting tools is a plus.
• A network in the AI drug discovery or computational biology community is a plus.

Education and Experience

• M.S. degree in a life science, bioinformatics, computational biology, or a related field with at least one year of sales experience; or B.S. degree in one of those fields with two or more years of experience in a related role.
• Experience in life sciences, a CRO, or a data or software company is strongly preferred.
• Experience selling biological data products or tools into pharma or biotech, such as genomic, transcriptomic, or clinically annotated datasets, real-world data, bioinformatics pipelines or platforms, or computational biology and AI/ML software, is preferred.