• The Lead Data Manager will be responsible for all data management activities in large, complex studies under general supervision • Primary communication point for project teams and company departments with regard to clinical data management • Coordination of data management activities within clinical projects related to EDC development, data collection, cleaning, reconciliation, Database Lock, development of final integrated database and generation of final Data Management deliverables • Primary responsibility for clinical data management activities within clinical projects • Study documents review • Data Management plan and other project-specific guidelines and instructions development and review • Co-ordinate/perform user acceptance testing • Development of Data Validation Plan/Edit Check Specifications • Data entry coordination and supervision • Data validation, including automatic and manual data inspections, data discrepancies/deficiencies review and resolution, query generation and resolution • Non-CRF electronic data handling • Database edits (paper CRF studies) • Manual CRF review (non-medical checks) • Clinical database lock • Coordination and supervision of processing, dispatch and archiving of CRFs/queries • Input into design of CRFs and other data collection forms; review Case Report Form design for accuracy and adherence to protocol • Development of CRF completion guidelines • Coding medical data with coding dictionaries and coding listings review • SAE reconciliation • Electronic data transfer specifications review and approval • Liaison with Document Center with regard to maintenance of TMF and eTMF • Database QC checks performance and documentation • Shared responsibility for preparation and attendance at internal and client/third-party audits/inspections of Data Management • Shared responsibility for follow-up on and resolution of audit findings pertaining to Data Management • Training of Assistant Data Managers • Project-specific training of investigators and clinical team in CRF completion

• Own the health, accuracy, and usability of data across our systems. • Manage and maintain data integrity across HubSpot and connected platforms, ensuring records are clean, deduplicated, and up to date. • Build and optimize HubSpot workflows, sequences, and automations to streamline operations and reduce manual processes. • Create and maintain dashboards, reports, and recurring data pulls for stakeholders across sales, marketing, and leadership. • Develop and enforce data governance standards, including naming conventions, property management, and lifecycle stage definitions. • Audit and troubleshoot data issues proactively—catch problems before they compound. • Own integrations between HubSpot and other tools in the stack (e.g., Zapier, Segment, spreadsheets, or internal databases). • Support ad hoc data requests and analysis for cross-functional teams, translating raw data into clear, actionable insights. • Document processes, SOPs, and system configurations so the team isn't reliant on tribal knowledge.

• Drive the definition and development of data science solutions to business problem statements from beginning to end: build relationships with partner teams, collect and analyze data, and develop recommendations to inform strategic decisions • Generate insights and recommendations through exploratory analysis, A/B testing, and statistical modeling • Work with product managers to design and analyze experiments to measure the impact of new features and develop a data-driven narrative on how their product is performing for use in monthly reviews • Collaborate with data producers and consumers during the product development lifecycle to ensure consistent data quality and availability for reporting post launch.

• Work in the Data Science team developing advanced AI solutions to drive marketplace growth and efficiency, leveraging cutting-edge technologies including GenAI and LLMs. • You will build models, tinker around them to make them work, test them, and eventually deploy them to production. You will see your stuff in action, and you will be able to measure the true impact of your models (less expected, yet a requirement) • You will maintain strong relationships with stakeholders. This means asking a lot of questions to business people and translating their requirements into achievable projects. It also means collaborating with other teams, like infrastructure and data engineering, to get things done in an elegant and timely manner. • Partner with Engineering and Product to deliver solutions (customer-facing and platforms) to our customers (internal and end customers) • Work with Product Analytics to track the KPIs of different ML use cases and measure the impact on our customers. • Partner with the Experimentation team to integrate the KPIs and their proxies into the Experimentation (A/B testing) platform. • You will work in multi-functional teams, in a diverse, multinational environment, filled with people from Portugal, Bulgaria, Romania, Poland and Ukraine. • Most importantly, you will have fun working with us :)