• Design, implement, and deploy predictive models and algorithms to inform sales strategies and drive measurable improvements. • Develop and maintain robust dashboards and analytics tools using SQL and business intelligence platforms such as Looker or Tableau. • Collaborate with go-to-market partners, including sales and marketing, to identify high-impact data science opportunities. • Communicate complex analyses and recommendations to technical and non-technical stakeholders, including presenting to executives. • Continuously refine metrics, measurement frameworks, and data pipelines to optimize accuracy and efficiency.

Role Description The Senior Clinical Data Manager (Sr. CDM) serves as the primary in‑house data management expert within a near-to-fully outsourced clinical execution model. This role provides strategic oversight and hands‑on leadership of all data management activities across the development programs in the Pharming portfolio. The goal of this role will be to ensure timely, accurate, and compliant data delivery across the Pharming portfolio. - Building fit for purpose data capture systems - Database cleaning - Coordination of third-party data transfers to facilitate trial reporting - Ensuring end‑to‑end data quality, SDTM/ADaM traceability, and accuracy of all statistical outputs Responsibilities - Provide expert guidance on data implications for protocol design, endpoints, and operational feasibility. - Act as the primary liaison between Pharming and vendor data management and biostatistics teams. - Review and approve CRO plans, including Data Management Plans, CRF completion guidelines, edit check specifications, and data review plans. - Oversee CRO and vendor performance, ensuring adherence to timelines, data quality standards, and contractual deliverables. - Partner closely with Clinical team members, Safety and Regulatory to ensure cross-functional alignment on data strategy. - Support the development of study-specific database builds using study protocol and configuration specifications, including performance of the User Acceptance Testing (UAT). - Review SAPs and TLF mock shells for feasibility, completeness, and alignment with collected data, ensuring complete end-to-end traceability: CRF → SDTM → ADaM → TLF outputs. - Periodically conduct targeted QC of key listings (e.g., AEs, SAEs, ConMeds, labs, vitals, exposure, efficacy assessments) to identify outliers, missing data, unexpected patterns, and data inconsistencies; drive their resolution with CROs. - Manage clinical data cleaning and delivery activities, including (soft) database lock, for interim analyses, DMC/DSMB reviews, and final CSR. - Ensure all data cut and database lock criteria are met and documented. - Ensure alignment between data management findings and statistical programming outputs. - Ensure AE/SAE data quality, including reconciliation with safety narratives and coding consistency (e.g., MedDRA). - Validate treatment-emergent flags, exposure metrics, and safety population definitions produced by CRO partners. - Lead TFL review workshops and data review meetings with Medical, Safety, and Clinical Ops. - Manage ad-hoc biostatistics and data requests from Health Authorities (e.g., FDA, EMA) during NDA/BLA review and coordinate rapid turnaround analyses and data outputs with CRO Biostats/Programming. - Support data output and review for medical and scientific presentations/publications. - Collaborate with Regulatory Affairs to track requests, ensure timely responses, and document resolutions. - Drive both strategy and delivery of all data management related items. - Other duties as assigned. Qualifications - At least 6 years of clinical data management experience in the pharmaceutical/biotech industry, preferably in a small biotech. - Bachelor’s or Master’s degree in a scientific or technical discipline. - Expertise with EDC systems (e.g., Rave, Veeva, Inform) and vendor data pipelines. - Solid understanding of SAS outputs, derivations, and dataset structures (SAS programming experience a plus but not required). - Proficiency with CDISC standards, Pinnacle 21, and submission metadata tools. - Experience using AI tools to enhance work product and increase efficiency. - Proven experience overseeing outsourced DM/Biostats activities. - Experience supporting regulatory submissions (NDA/BLA) preferred. - Commitment and alignment to Pharming’s mission, core values and behaviors. Salary Range The base salary range for this job is from $130,000 to $170,000 per year. Pharming takes into consideration a combination of candidate’s work experience, training, and education, as well as the scope of the role, complexity, and external market and internal value when determining a salary level. Benefits - A fully remote work schedule - Competitive compensation package including annual target bonus - Long-term incentive program - 401(k) plan with company match - Paid Time Off (PTO) - 13 Company Holidays per year - Excellent benefit plans including medical, dental, and vision - Flexible spending accounts - Company-provided life insurance, short-term disability, and long-term disability plans - Optional accident, hospital indemnity, critical illness, and pet insurance plans - Tuition reimbursement program - Health and wellness program - Choice of company provided mobile phone or cell phone stipend

Role Description As a Data Scientist, you will be required to lead the development of distinctive analytical and risk insights that deliver improvements in business results and customer experience through the application of advanced data science techniques to complex data sets. Your main responsibilities will involve: - Lead discussion with the business stakeholders from better defining the problem and best suitable solution, up to building and delivering end-to-end solutions, and ensuring successful delivery of benefits in production to improve customer engagement, business processes, and product enhancements. - Establish, maintain, and grow strong, collaborative relationships with key internal and external partners; leverage relationships to drive ongoing improvements to the data and data architecture. - Play an active role in generating distinctive analytical and risk insights for the most complex and/or strategic business challenges and opportunities, including synthesizing insights into compelling ideas and messages. - Lead and own the technical architecture of the data platform in production, and drive processes and system improvement to enhance performance and optimize costs. - Drive the development of next-generation, market-leading analytic techniques to build the capabilities of the Data Science Center of Excellence for APAC. Qualifications - Bachelor degree in related fields and/or more years of experience in data science. - Lead and implemented data science use cases and delivered measurable benefits. - Advanced knowledge of statistical and predictive modelling techniques such as machine learning, decision trees, probability networks, clustering, neural networks. - Minimum 2 years’ hands-on experience in unstructured data, including natural language processing, image recognition, OCR, voice to text, etc. - Experience in deploying solutions in production (Azure, AWS). - Expert user in Python and data wrangling packages. - Familiar with MLOps, API Development (FastAPI, etc.). - Experience with AI Agents Observability & Performance Monitoring: reporting on key performance metrics to maintain reliability and optimize outcomes. - Data science experience in similar industry (e.g. insurance, financial services) preferred. Company Description Zurich Insurance has the policy to be an equal opportunity employer. We aim to attract and retain the best qualified individuals available, without regard to criteria such as race/ethnicity, national origin, religion, gender, sexual orientation, age or disability. At Zurich we believe that having a culture of inclusion is essential in delivering good results. Attracting, retaining and developing a diverse workforce where employees feel valued, respected and empowered allows people to reach their full potential. As a business, this diversity helps us to better reflect and understand our 4 million customers’ needs to allow us to drive better outcomes. As a global organization, with an increasingly agile workforce, we're happy to consider flexible working arrangements.

• Partner closely across the business to find improvements/opportunities and influence decisions using data analytics methodologies and tools. • Act as the data owner for Finance functions, including but not limited to accounting, tax, strategic finance, profitability, and the executive office. • Build production-quality data products, dashboards, notebooks, and actionable KPIs to convey critical financial insights. • Drive incremental improvements in contribution margin by deeply understanding business drivers and analyzing cross-functional initiatives. • Collaborate on data and analytics engineering work to ensure financial datasets are enriched, reliable, and scalable.