• Designing and developing bidding and optimization strategies for CPC-based auction systems, including advanced objectives such as target ROAS • Optimizing auction mechanisms (ranking, pricing, filtering) to balance platform revenue, advertiser value, and marketplace stability • Building and maintaining offline simulation environments, including counterfactual simulations and auction replay systems, to safely evaluate algorithmic changes • Designing and implementing feedback loops and control mechanisms to ensure stable and robust system behavior under dynamic market conditions • Conducting advanced ecosystem-level analytics on large-scale datasets to identify nonlinear effects, equilibrium points, and systemic risks • Designing, executing, and analyzing complex experiments and causal inference studies, accounting for network effects and long-term system impact • Contributing to the evolution toward smart, autonomous bidding and auction optimization through data-driven initiatives and roadmap development

• Designing and developing bidding and optimization strategies for CPC-based auction systems • Optimizing auction mechanisms to balance platform revenue, advertiser value, and marketplace stability • Building and maintaining offline simulation environments to safely evaluate algorithmic changes • Conducting advanced ecosystem-level analytics on large-scale datasets • Designing, executing, and analyzing complex experiments and causal inference studies • Contributing to the evolution toward smart, autonomous bidding and auction optimization

• Data Management POC for studies in which we are included in • Responsible for mapping local study dictionaries to CDISC Standards • Participate and contribute to the development of operational plans to ensure data quality and completeness • Develop, Implement, and Conduct data quality checks as needed for work/studies • Work closely with the various stakeholders to understand evolving project portfolio needs, and integration into the systems and requirements; supporting studies with a wide range of disease domains • Contribute technical expertise toward the design, implementation, and scaling up of sensor systems and analytics • As a medical informaticist, ensure collection, organization, curation, storage and safeguarding of patient data from lab, asset teams, and external collaboration studies is consistent with 21CFR part 11 • Contribute to the overall architecture of the existing data pipelines and workflows, recommends and implements improvements • Track emerging study data and works closely with data science team to ensure the effectiveness of tools and data quality • Manage own time to meet agreed targets • Work under general supervision. Performs assignments using established procedures and general instruction • Share learnings with key stakeholders and the scientific community through presentations and peer-reviewed publications

• Lead all aspects of data management for medical device clinical trials, ensuring compliance with FDA, MDR, ICH-GCP, and ISO 14155 regulations. • Develop and maintain Data Management Plans (DMPs) and Case Report Forms (CRFs) aligned with study protocols. • Design, validate, and manage Electronic Data Capture (EDC) systems such as Medidata RAVE, Oracle InForm, or Veeva Vault EDC. • Oversee data cleaning, query management, and reconciliation processes to ensure high-quality, analyzable datasets. • Ensure adherence to CDISC/CDASH/SDTM standards, enabling efficient regulatory submission. • Conduct and support data audits, quality control (QC) reviews, and database lock activities. • Serve as the data management lead for multiple studies, collaborating with cross-functional teams including clinical operations, biostatistics, and regulatory affairs. • Manage relationships with CROs, vendors, and external data management teams, ensuring alignment with project timelines and quality standards.