Job Description
About Signant Health
At Signant Health, we help bring life-changing treatments to patients faster. We are a global evidence generation company that supports clinical trials with smart technology, scientific expertise, and hands-on operational support — so better data leads to better decisions in healthcare. We embrace AI and advanced technologies to enhance every aspect of what we do, from data analysis to operational efficiency.
Our teams work at the intersection of science, technology, and patient experience, delivering digital solutions powered by AI innovation that make clinical trials more efficient, more accurate, and more accessible around the world. Trusted by leading pharmaceutical companies and CROs, our platforms and services support studies across more than 90 countries and have contributed to hundreds of new drug approvals.
If you are motivated by meaningful work, global impact, and innovation in clinical research and digital health — including the opportunity to work with cutting-edge AI technologies — you will find purpose and opportunity at Signant Health.
About the Role:
Embedded within the Product Management function, this role owns the end to end data science capability that powers products growing Intelligence Layer. The Senior Clinical Data Scientist – Product Management translates product vision into working AI and ML systems from supporting the shaping of roadmap priorities to building and shipping models ready for production.
This is not an analytics or reporting role. It sits at the intersection of clinical data science, AI engineering, and product strategy, and requires someone who can speak the language of clinical trials, own a machine learning pipeline, and translate complex model outputs into clear insight for product, clinical, and engineering teams.
What you will do:
• Partner with Product Director/Manager(s) to translate clinical risk monitoring requirements and quality standards into AI-powered features that reduce reliance on manual data science effort.
• Design and build production-ready ML models end-to-end, owning the full lifecycle from data pipeline through MLOps, in close collaboration with software engineering to deploy models into validated clinical systems.
• Build and iterate on agentic AI capabilities within the data platform, including conversational interfaces and automated signal detection agents that surface actionable insights without manual intervention.
• Own statistical and anomaly detection models that identify data integrity risks and site-level performance signals, consistent with ICH E6(R3) and RBQM regulatory expectations.
• Develop ML models for clinical workflow quality, detecting patterns indicative of rater inconsistency, assessment quality issues, and data anomalies across therapeutic areas including CNS, oncology, and rare disease.
• Define and maintain the feature store and MLOps infrastructure underpinning all AI capabilities.
• Translate complex model outputs into clear, actionable insights for clinical, commercial, and sponsor audiences.
• Contribute to roadmap prioritization by evaluating technical feasibility, data readiness, and model viability of proposed AI initiatives.
• Monitor and incorporate relevant advances in LLMs, agentic AI, and clinical data science into the product.
• Collaborate cross-functionally with engineering, clinical science, and data platform teams to ensure data quality and governance support AI delivery.
Preferred Qualifications:
• Proficiency in Python and SQL, able to build and own production pipelines, not just analytical notebooks.
• Hands on experience building production ready ML models end to end, including data pipelines, model development, and MLOps, with experience working alongside software engineering for deployment into validated or regulated systems.
• Practical experience with LLMs, generative AI, or agentic AI systems, prompt engineering, RAG, or orchestration frameworks.
• Experience with MLOps, model versioning, monitoring, drift detection, and retraining pipelines.
• Strong statistical foundation, anomaly detection, classification, time series analysis.
• Experience working embedded within a product or engineering team, not a standalone data science function.
• Ability to communicate model outputs, data findings, and technical constraints clearly to non-technical stakeholders including commercial and clinical teams.
• Understanding of clinical trial data structures including eCOA, EDC, CTMS, and CDISC standards (SDTM, ADaM) and familiarity with Risk-Based Quality Management (RBQM), and Key Risk Indicator frameworks as defined under ICH E6(R3).
• Strong product thinking, able to define what to build and why, not just execute on a specification.
• Experience with cloud data platforms, Snowflake, Databricks, AWS, or Azure equivalent.
Desired Qualifications:
• Direct experience in clinical trials, pharma, or digital health, particularly in centralised statistical monitoring, RBQM platforms (e.g. CluePoints, Medidata RBQM, Veeva Vault), rater-based assessments, or eCOA data quality analytics
• Experience building or working with fraud detection or data fabrication identification systems in regulated clinical data environments, including timestamp analysis, duplicate patient detection, or site outlier scoring consistent with FDA/EMA RBQM guidance
• Familiarity with dbt, data lineage, or medallion architecture patterns
• Experience with voice or acoustic ML models
• Prior experience influencing product roadmap decisions with data science evidence
Why Signant Health?
At Signant Health, your work has real impact. Everything we build, support, and deliver helps advance clinical research and bring new treatments to patients faster — improving lives around the world. Our teams combine science, technology, and operational expertise to solve complex clinical trial challenges, and every role contributes to that mission.
We offer a collaborative, global environment where you can grow your career while working alongside experts across clinical, technology, data, and operations, with opportunities to learn, take ownership, and drive meaningful innovation — not just maintain the status quo.
If you are looking for purpose-driven work, smart colleagues, and the opportunity to help shape the future of clinical research and digital health, Signant Health is the place to do it.
At Signant Health, accepting difference isn't enough — we celebrate it, we support it, and we nurture it for the benefit of our team members, our clients, and our community. We are proud to be an equal opportunity workplace and an affirmative action employer, committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status. Prior to their start date, all candidates are required to be verified through a thorough background check and identity verification to confirm eligibility for employment.
