
Powerful, integrated real-world data and AI-driven solutions to transform how insights are generated and accelerate therapeutic innovations to patients.

Powerful, integrated real-world data and AI-driven solutions to transform how insights are generated and accelerate therapeutic innovations to patients.
Core focus: Oncology real-world data (RWD) and AI-driven solutions for research, clinical development, regulatory evidence, and commercial teams
Product highlights: Precision Suite (PrecisionExplorer, PrecisionTRIALS, PrecisionGTM, Precision360), CancerLinQ, TeraRecon imaging, CARAai
Headcount: 871 employees (source snapshot)
Investor backing: Backed by SAI / SymphonyAI and institutional growth investors including Sixth Street and Declaration Partners
Generating and analyzing oncology real-world data and applying AI to accelerate clinical development, regulatory evidence, and commercial strategy.
2018
Healthcare / Life Sciences / Health AI
Company profiles record a Series C funding round.
“Backed by SAI Group / SymphonyAI, Sixth Street, Declaration Partners, Maverick Ventures, and AllianceBernstein Private Credit Investors”
Job Requirements Role Summary: ConcertAI is seeking a Data Scientist to join our Client Services team within the Real World Evidence (RWE) Business Unit. This client-facing role will focus on supporting the successful delivery and ongoing support of ConcertAI’s data products, including EHR, claims, and multi-modal real-world datasets, as well as support for ConcertAI's new suite of AI-driven data and platform products. You’ll work closely with pharmaceutical and biotechnology partners to ensure optimal value and usability of our products within their analytic workflows. As a key technical contributor, you will drive solution implementation, respond to data inquiries, enhance analytic delivery pipelines, and act as a bridge between client needs and internal data engineering, product, and informatics teams. Most work will involve SQL (primarily in Redshift), with opportunities to leverage R, dbt, and Python. Responsibilities: * Serve as a client-facing data scientist supporting the implementation and use of ConcertAI’s real-world data products. * Provide analytic and technical support for client onboarding, training, and ongoing data product usage. * Write performant SQL to generate analytic outputs, assess data quality, and respond to client questions. * Create reusable, well-documented code assets to scale support across clients. * Support internal and external teams by transforming business logic into scalable queries and data models. * Collaborate with internal teams (Epidemiology/HEOR, Data Operations, Informatics, Engineering) to troubleshoot issues and enhance product functionality. * Translate complex technical outputs into actionable insights for client stakeholders. * Work cross-functionally with Product, Engineering, and Client Partners to ensure high-quality, timely delivery of analytic solutions. * Maintain clear documentation and knowledge-sharing across engagements. * Contribute to product enhancements through feedback loops informed by client use and data exploration. Work Experience Qualifications: * Bachelor’s or Master’s degree in a quantitative discipline (e.g., Data Science, Biostatistics, Computer Science, Epidemiology) or equivalent experience. * 3+ years of experience in a data-focused role within life sciences, healthcare, or biotech. * Experience working with real-world data (claims, EHR, or similar). * Strong SQL skills (preferably Redshift), with experience building data pipelines and analytic queries. * Experience with R and/or Python for data manipulation and statistical analysis. * Strong communication and stakeholder management skills, with the ability to explain complex data issues clearly to technical and non-technical audiences. * Ability to manage multiple client needs simultaneously in a fast-paced, client-centric environment. * Comfortable with ambiguity and eager to learn new tools and domains quickly. Nice to Have: * Experience supporting productized data or SaaS offerings. * Experience working on client-facing RWD or RWE projects. * Oncology domain expertise. * Familiarity with agile workflows and collaborative version control (e.g., Git). * Familiarity with modern data engineering tools (e.g., dbt, Airflow, Snowflake, Redshift).
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