Senior Applied Data Scientist, Pharma

Spectrum Search is partnered with an established AI technology company helping healthcare and life sciences organisations turn complex data into measurable commercial outcomes. This opportunity combines hands-on machine learning engineering with ownership of pharmaceutical client delivery. About the opportunity The company develops applied AI solutions that support commercial decision-making across healthcare and life sciences. Profitable and well-backed, it offers the opportunity to build production systems, work directly with senior customers and influence product development. The team is seeking a Senior Applied Data Scientist who understands pharmaceutical commercial operations and can translate business questions into robust models, deployed pipelines and clear recommendations. The role This is a full-time, hands-on position covering the complete client delivery lifecycle, from discovery and technical scoping through development, production deployment and ongoing improvement. The successful candidate will work closely with pharmaceutical brand teams, commercial operations, field leadership, data science and IT. They will combine technical delivery with the communication skills to lead working sessions, challenge assumptions and defend analytical findings. Key responsibilities Own technical delivery for client accounts, including discovery, solution design, model development, integration and production deployment. Understand each client’s therapeutic area, patient journey, field structure and commercial constraints. Translate commercial questions into clearly defined data science problems and measurable outcomes. Build predictive models supporting healthcare professional identification, prioritisation, switching prediction and territory planning. Develop production-grade data and machine learning pipelines, including feature engineering, evaluation and monitoring. Design and defend experimental studies that assess commercial impact. Present findings and recommendations to senior stakeholders, explaining methodological choices and limitations. Navigate privacy, data governance and medical, legal and regulatory review requirements. Convert deployment insights into reusable tooling and product improvements. Essential requirements A track record of delivering production systems in customer-facing data science, machine learning engineering or technical solutions roles. Hands-on experience solving commercial problems for pharmaceutical or life sciences organisations, including targeting, field-force enablement or commercial analytics. Strong Python and SQL skills, with the ability to take models from exploratory analysis into deployed pipelines. Practical experience building and evaluating predictive models. Experience with cloud platforms such as AWS, GCP or Azure and modern data platforms such as Snowflake, Databricks or BigQuery. Knowledge of pharmaceutical commercial datasets, including prescription data, provider identifiers, healthcare professional affiliations, specialty pharmacy and field customer relationship management systems. Strong client-facing communication, including leading technical discussions and presenting to senior pharmaceutical stakeholders. The ability to work independently through ambiguous requirements and take responsibility for delivery quality. Nice-to-haves Experience with rare disease or specialty product launches. Experience operating in regulated data environments. Familiarity with PySpark, Spark, Airflow, pandas or scikit-learn. Experience building large language model systems or AI agents. Experience building and scaling systems within a startup. Location and remote setup US-based remote position, with Eastern or Central working hours preferred. The role includes quarterly team offsites in New York and occasional client travel, approximately 10%. Applicants must have US work authorisation that does not require visa sponsorship. Sponsorship is unavailable.