AI and ML Manager

Company Description
Ergomed is a rapidly expanding full service mid-sized CRO specialising in Oncology and Rare Disease.

Since its foundation in 1997 the company has grown organically and steadily by making strategic investments and landmark acquisitions, with operations in Europe, North America and Asia

Our company allows for employee visibility (you have a voice) creative contribution and realistic career development.

We have nourished a true international culture here at Ergomed.

We value employee experience, well-being and mental health and we acknowledge that a healthy work life balance is a critical factor for employee satisfaction and in turn nurtures an environment from which a high-quality client service can be achieved.

Come and join us in this exciting journey to make a positive impact in patient's lives.

Job Description
Key Responsibilities
Strategy & Governance

• Define and execute the AI/ML roadmap aligned to clinical, PV, and quality/audit objectives (e.g., site selection, patient recruitment, signal detection, case intake automation, RBQM).
• Run an AI opportunities and triage process (use‑case assessment, value/risk scoring, resourcing, and portfolio tracking).
• Establish AI governance: model risk classification, validation/qualification plans, algorithm change control, documentation (model cards, datasheets), and monitoring.
• Ensure compliance with GxP, 21 CFR Part 11/Annex 11, ICH E6(R3), GVP for PV, data privacy (GDPR/PHI), and vendor and Ergomed IT and security standards.
• Define and track KPIs (e.g., model adoption, cycle-time reduction, accuracy/recall, signal sensitivity/specificity, audit findings, cost-to-serve).

Solution Design & Delivery

• Understands and translates business and functional needs into AI and machine learning problem statements
• Translates complex AI and machine learning problem statements into specific deliverables and requirements
• Designs and develops scalable solutions that leverage machine learning and deep learning models to meet Ergomed business requirements
• Performs tasks such as data normalization, feature selection, dimensionality reduction, and handling missing or outlier data to ensure data quality and relevance
• Works closely with business, process analysts and data engineers to frame business problems and need into AI/ML product or workflow. Collaborates with development teams to test and deploy machine learning models
• Evaluate models' performance, conduct cross-validation, and use metrics such as accuracy, precision, recall, or F1-score to assess model quality
• Monitor the performance of deployed models, track data or concept drift, and update or retrain models as needed
• Stays updated with the latest advancements in AI and ML technologies to identify their potential applications in the Ergomed business model and internal processes improvements

Data Standards, Quality & Interoperability

• Knowledge and understanding of use of CDISC SDTM/ADaM, HL7 FHIR, MedDRA, WHODrug, and SNOMED CT.
• Establish robust data quality frameworks (profiling, completeness, timeliness, conformance checks) and FAIR data principles.
• Oversee PHI/PII handling, de-identification, and secure data access patterns (role-based access, least privilege).

Execution Coordination & Stakeholder Management

• Educate, mentor, and grow more junior data scientists, ML engineers, and AI specialists; cultivate a culture of scientific rigor, design-for-compliance, and continuous learning.
• Partner with Clinical Ops, PV/Drug Safety, Biostatistics, Regulatory, QA, IT/Security, and commercial client teams to translate needs into high-value AI solutions.
• Collaborate and cooperate with external partners and vendors and ensure SOWs, SLAs, and validation deliverables meet compliance and performance expectations.

• Oversee design, development, validation, and deployment of ML/NLP/GenAI solutions for:

• Clinical Operations: protocol feasibility, site and investigator selection, patient eligibility/matching, country start-up forecasting, RBQM/central monitoring, query reduction.

• Pharmacovigilance: ICSR intake/triage (NLP), de-duplication, case validity checks, literature screening, medical coding support, signal detection & prioritization, causality/seriousness assistance (human-in-the-loop).
• Regulatory & Quality: authoring support for submissions and SOPs (GenAI with RAG), audit analytics, inspection readiness dashboards, document classification in eTMF/CTMS.

• RWD/RWE & Safety Analytics: EHR/claims ingestion, de-identification, pseudonymization, cohort building, outcomes and safety signal analytics.

• Ensure solutions integrate with existing platforms (e.g., EDC, CTMS, eTMF, Safety DBs like Argus/LifeSphere, Veeva stacks, Ergomed analytical data platform and BI tool).

• Drive MLOps in a regulated setting: CI/CD for models, feature stores, reproducible pipelines, lineage/metadata, monitoring (data, drift, performance), and rollback.
• Communicate complex AI concepts and model risk/impact to executive and non-technical stakeholders with clarity and accountability.

Qualifications
Job Requirements
Education

• Bachelor's degree in computer science, data science, engineering, biostatistics, or related field (master's or Ph.D. preferred).
• Desirable: coursework or certification in GxP/CSV, biostatistics, clinical trials, pharmacovigilance, or regulatory affairs.

Experience

• 7–10+ years in applied AI/ML (including NLP/GenAI), with 2–4+ years coordinating cross-functional teams or programs.
• Demonstrated delivery of production AI products within business processes.
• Hands-on leadership of MLOps and lifecycle management in cloud (AWS, GCP, Azure); experience with Azure ML, Databricks, Synapse/Fabric, MLflow
• Experience integrating with life sciences systems (e.g., EDC: Medidata/Oracle; CTMS/eTMF: Veeva; Safety: Argus/LifeSphere; BI: Power BI).
• Experience in creating agentic, multi-agent AI solutions.

Preferred/Bonus

• Experience with RWD/RWE, de-identification, privacy engineering.
• Knowledge of ICH E6(R3), GVP Modules, MedDRA/WHODrug coding, and CDISC implementation.
• Familiarity with EU AI Act considerations for high-risk systems and internal Model Risk Management frameworks.

Skills

• Technical:

• Python, SQL; ML frameworks (scikit-learn, XGBoost, PyTorch/TensorFlow); NLP/LLMs (Transformers, RAG, prompt engineering, evaluation).

• Data engineering (Spark), pipelines/orchestration (e.g., Azure Data Factory, DataBricks, Fabric LakeHouse, Airflow), feature stores, containers (Docker/Kubernetes).
• MLOps (MLflow/Azure ML), experiment tracking, monitoring, CI/CD, testing, and observability.
• BI & analytics (e.g., Power BI, Tableau, QlikSense), statistical methods (sampling, hypothesis testing, time series, survival/longitudinal analysis a plus).

• Interoperability & standards (CDISC, FHIR, MedDRA, WHODrug); data privacy (GDPR/PHI) and de-identification.

• Compliance & Quality:

• Computerized System Validation (CSV), documentation discipline, traceability, audit trail management, change control, SOP authorship.

• Bias/explainability tools, human-in-the-loop controls, risk assessments, and control design for regulated AI.

• Leadership & Communication:

• Team building and mentoring; stakeholder engagement across Clinical Ops, PV, QA, and Regulatory.

• Clear communication of risk/benefit, assumptions, limitations, and model performance to non-technical audiences.
• Product mindset—translating user needs into validated, usable solutions with measurable outcomes.

Additional Information

We prioritize diversity, equity, and inclusion by creating an equal opportunities workplace and a human-centric environment where people of all cultural backgrounds, genders and ages can contribute and grow.

To succeed we must work together with a human first approach. Why? because our people are our greatest strength leading to our continued success on improving the lives of those around us.

We Offer

• Training and career development opportunities internally
• Strong emphasis on personal and professional growth
• Friendly, supportive working environment
• Opportunity to work with colleagues based all over the world, with English as the company language

Our core values are key to how we operate, and if you feel they resonate with you then Ergomed is a great company to join

Quality

Integrity & Trust

Drive & Passion

Agility & Responsiveness

Belonging

Collaborative Partnerships

We look forward to welcoming your application.

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