Medical Science Liaison; MSL

Founded in 2018, xCures operates the leading healthcare data platform, which can aggregate medical records from various sources, normalize and structure them for processing. Assisted by artificial intelligence, the platform extracts data to provide healthcare providers and diagnostics with fast and easy access to the specific clinical information needed to deliver care.

xCures is seeking an experienced, analytical, and driven Medical Science Liaison (MSL) to join our growing team. Reporting to the Vice President of Scientific and Medical Affairs, you will serve a critical role providing medical and scientific support for our Customer Success team on key accounts, playing a pivotal part in maximizing client engagement and satisfaction. You will ensure clients fully understand the nuances of data generated by our platform and optimize its application for their research and clinical needs.

You will also articulate client needs to internal Data Science, Product, and Engineering teams to ensure client delight. Outstanding communication and project management skills are essential with an ability to manage multiple complex and unrelated projects simultaneously. Comfort in a remote, fast-paced, growth-phase start-up environment is paramount.

• Serve as a key scientific liaison in client and partner discussions, helping to define data needs, manage expectations, and translate clinical and operational requirements into actionable strategies, ensuring alignment with xCures’ technical capabilities.
• Lead external discussions around data quality and validation and communicate complex clinical data extraction capabilities and insights (e.g., genomics, oncology treatments, patient outcomes), ensuring clear understanding of product features and scientific accuracy.
• Act as a subject matter expert in oncology and real-world data applications during client meetings and external engagements.
• Support client research initiatives by advising on the interpretation, provenance, and internal use of real-world data (RWD), including data extracted through AI/ML algorithms such as large language models.
• Provide scientific guidance on the design and execution of client-led real-world evidence studies utilizing xCures’ platform.
• Assist clients in troubleshooting data-related queries and provide scientific explanations for data anomalies or findings.
• Collaborate with internal product and engineering teams to inform the development of client-facing features and data offerings based on external medical and scientific requirements.
• Perform ongoing review of data products to ensure they meet scientific standards, client expectations, and regulatory considerations.
• Propose and lead collaborations on joint publications and thought leadership efforts with clients and external researchers.
• Represent xCures at conferences and external forums by presenting on platform capabilities, scientific findings, and applications of RWD in oncology, in support of the business development team.

Required Qualifications:

• PhD in a life sciences discipline
• 4+ years of experience as an MSL in the oncology diagnostics industry
• Demonstrated ability to translate complex scientific concepts into clear, concise, and actionable insights for diverse audiences
• Proven ability to build and maintain strong professional relationships with diverse stakeholders, including clients, academic researchers, and internal cross-functional teams (e.g., product, engineering, business development)
• Experience with structured clinical data and real-world data analysis
• Proven track record of managing multiple complex and unrelated projects simultaneously, with strong organizational and time management skills
• Exceptional communication (written and verbal) and presentation skills
• Comfort working remotely and with virtual communication platforms
• Ability to thrive in a fast-paced, dynamic, and growth-phase start-up environment

Preferred Qualifications:

• Significant experience with electronic medical records (EMR) and a deep understanding of the current healthcare data landscape (e.g., Health Information Exchanges (HIE), Qualified Health Information…