• Lead the design, development, deployment, and optimization of machine learning, predictive analytics, and AI-powered solutions. • Translate business challenges and opportunities into analytical approaches, model specifications, and measurable success criteria. • Apply advanced statistical analysis, machine learning techniques, and data science methodologies to solve complex business problems. • Analyze large, complex datasets to identify trends, patterns, opportunities, and actionable insights. • Develop and maintain model documentation, technical specifications, and implementation plans. • Stay current with emerging technologies, tools, and best practices in data science, machine learning, and artificial intelligence. • Design and execute comprehensive validation and evaluation strategies for machine learning and generative AI solutions. • Develop benchmarking frameworks and success metrics to assess model performance, reliability, and business impact. • Evaluate model quality using quantitative and qualitative measures, including accuracy, precision, recall, robustness, latency, and business outcome metrics. • Assess generative AI applications for response quality, grounding, relevance, consistency, and hallucination risk. • Identify and mitigate risks related to bias, fairness, explainability, privacy, and model reliability. • Perform model validation, testing, and performance assessments prior to production deployment. • Establish monitoring processes and evaluation methodologies to ensure continued model effectiveness and alignment with business objectives. • Design, execute, and analyze experiments, including A/B tests and statistical studies, to measure product and business outcomes. • Define key performance indicators and success metrics for machine learning and AI initiatives. • Measure and communicate the impact of analytical solutions through statistical analysis and quantitative methods. • Partner with stakeholders to define hypotheses, success criteria, and decision-making frameworks. • Use experimentation and data-driven insights to guide product, operational, and strategic decisions. • Collaborate with Engineering and Data Engineering teams to implement, operationalize, and scale models in production environments. • Monitor deployed models for performance degradation, model drift, data quality issues, and changing business conditions. • Recommend retraining, optimization, or replacement strategies based on model performance and evolving business needs. • Support the creation of scalable, maintainable, and reliable AI and machine learning solutions. • Ensure model deployment processes align with engineering best practices and operational requirements. • Partner with Product, Engineering, Analytics, and business stakeholders to prioritize opportunities and deliver high-impact solutions. • Communicate complex analytical findings and technical concepts to both technical and non-technical audiences. • Present recommendations, insights, and model performance results to leadership and project teams. • Support technical reviews, project planning, and delivery activities across cross-functional initiatives. • Contribute to knowledge sharing, documentation, and best practices within the data science organization. • Provide technical guidance and mentorship to junior team members and peers as needed.

• Deliver comprehensive data management services across all study phases • Independently own assigned data management studies and deliverables from startup through database lock, proactively identifying risks, resolving issues, communicating status, and escalating when appropriate • Ensure clinical databases are complete, accurate, and compliant with Sponsor and regulatory standards • Serve as primary Sponsor contact for data management activities • Lead data management communications and coordinate with internal and external teams to ensure timely delivery of study milestones and progress updates • Train site staff (CRCs, CRAs, PIs) and client teams on EDC systems • Oversee CRF lifecycle from design to final delivery • Conduct User Acceptance Testing (UAT) and ensure database setup aligns with specifications • Develop and manage essential study documents (e.g., Data Management Plan, CRF Completion Guidelines, Validation Plans, SAE Reconciliation Plans) • Review and clean clinical data, manage queries, and reconcile third-party data • Coordinate database lock and final data delivery • Identify risks and proactively resolve project issues • Provide exceptional service to internal and external stakeholders

• Partner with Product, Engineering, Design, and Operations to inform and shape product strategy, prioritization, and decision-making • Develop metrics, data models, and analytical frameworks that improve how teams understand customer behaviour and business performance • Identify opportunities to improve customer experience, growth, retention, and operational efficiency through data • Translate complex business questions into clear recommendations and actionable insights • Proactively surface trends, risks, and opportunities that help the team focus on the highest-impact work • Collaborate with Analytics Engineering to improve the quality, scalability, and usability of data foundations for the team

Role Description Terray Therapeutics is seeking a highly motivated and experienced in vivo scientist with expertise in models of autoimmunity and inflammation to join our Translational Biology team. In this role, the candidate will serve as a scientific and operational lead for outsourced in vivo pharmacology and nonclinical safety/toxicology studies, with responsibilities including study design, execution and monitoring, vendor oversight, project management and cross-functional coordination. The position will report to the Director of Translational Biology. - Provide scientific leadership and oversight for in vivo pharmacology studies focused on inflammation, autoimmunity, or related therapeutic areas in support of advancing our pipeline programs. - As the pharmacology representative, collaborate cross-functionally with preclinical teams, project leads, and external consultants to advance our pipeline programs through in vivo studies. - Lead and monitor outsourced in vivo pharmacology and nonclinical safety/toxicity studies conducted at CROs, ensuring scientific rigor, protocol compliance, data quality, and timely execution. - Contribute to study design, protocol development and review, endpoint selection and data interpretation. - Review study reports, datasets and summaries to ensure scientific accuracy and completeness. - Coordinate study timelines, logistics, milestones, budgets and deliverables across multiple external vendors and internal stakeholders. - Manage CRO relationships, including vendor selection, performance oversight, issue resolution and communication. - Maintain study documentation, ensuring compliance with regulatory requirements and company policies. - Present study updates and recommendations to project teams and leads. - Support contract management activities (scopes of work, purchase orders, invoice tracking). Qualifications - Ph.D. degree in biology, immunology, pharmacology, toxicology, or a related field. - 3+ years of experience in biotech or pharmaceutical industry supporting nonclinical drug development programs. - Strong scientific background in inflammation, immunology, or immune-related diseases. - Extensive experience with rodent in vivo pharmacology and translational disease models. - Strong scientific data analysis, interpretation, and problem-solving skills. - Strong understanding of nonclinical drug development workflow. - Experience managing or monitoring outsourced studies at CROs. - Demonstrated project management and organizational skills with the ability to manage multiple studies and priorities simultaneously. - Excellent written, verbal, and presentation skills. - Ability to work effectively in cross-functional teams and to thrive in a highly collaborative research environment. Requirements - Experience with vendor oversight, contract management, and budget tracking. - Experience supporting IND-enabling and preclinical development programs. - Knowledge of GLP and non-GLP study conduct and non-clinical assessment. - Familiarity with IACUC regulations and animal welfare standards. Benefits - Compensation: $120,000 – $175,000 annually, depending on experience. - Participation in the Company’s stock option plan. - 3% retirement safe harbor contribution. - Fully paid health, dental, vision insurance for employees, spouses, partners, and families. - Above-market life insurance and disability coverage. - Additional benefits to explore during the offer process.