- Collaborate on the redesign and optimization of end-to-end data management processes including study start-up, maintenance, and close-out. - Evaluate and revise existing procedures to align with internal execution capabilities, ensuring operational efficiency, compliance, and scalability. - Provide strategic oversight of functional improvements across data management operations. **Functional Area Ownership** - Oversee and contribute to the reengineering and execution of critical data management functions, including: - Study Set-Up - EDC Build and Maintenance - Data Cleaning and Query Management - Local Laboratory and External Data Handling - Clinical Coding - SAE Reconciliation - Blinding Procedures - Site Close-Out and Database Lock - Data Management Metrics and Clean Patient Tracker oversight **Quality & Compliance** - Ensure all data management activities comply with applicable regulatory requirements, CDISC standards, and internal quality standards. - Support audit readiness, inspection preparedness, and continuous quality improvement initiatives. - Identify and mitigate data-related risks proactively. **Clinical Trial Leadership & Cross-Functional Collaboration** - Represent the Data Management function within the clinical trial working group. - Ensure aligned expectations for all data-related deliverables, especially those supporting regulatory submissions and key milestone decisions. - Collaborate closely with Clinical Operations, Statistical Programming, Biostatistics, and other stakeholders to ensure timely database lock and delivery of high-quality data. - Provide influential leadership to ensure milestones and deliverables are met within timelines and budget. - Contribute to continuous improvement initiatives at the functional and organizational levels.

• Refining and supporting adoption of AI agents that can summarize performance, detect anomalies, and suggest remediations • Tailoring our models to customer strategy, whether it’s growing sales in a new category or maximizing profit in a challenging one • Designing, running, and analyzing experiments to improve customer performance • Providing visibility into ordering issues like fill rates, short dated product, or produce quality concerns • Collaborating with the core Crisp Data Science team on model enhancements to address customer needs

• Maintains a personal relationship with Jesus Christ • Develops, analyzes, and models operational, program, marketing, or other organizational data to analyze the competitive performance of Compassion's business segments • Develops innovative strategies, quantifies the competitive performance of the organization's operations and/or markets • Further evaluates potential operational changes, and designs new approaches and data methodologies accordingly • Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high volume data from a variety of sources • Further tests and troubleshoots internal advanced analytics tools and data programs • Works closely with vendors to manage maintenance of data modeling tools • Performs exploratory data analysis to understand relationships, opportunities to influence outcomes and how to attribute cross-channel outcomes • Further develops proofs of concept to verify ideas and closes the loop to make sure that the proposed solution is performing as it should and is correctly understood by clients • Translates complex analytical and technical concepts for non-technical team members to enable understanding and drive informed business decisions • Collaborates with cross-functional teams across the organization to support data and cloud computing strategies

Dstillery is the leading AI ad targeting company. We empower brands and agencies to target their best prospects for high-performing programmatic advertising campaigns. Backed by our award-winning Data Science, Dstillery has earned 24 patents (and counting) for the AI technology that powers our precise, scalable audiences. Our newest technology, ID-free®, is patented, privacy-safe behavioral targeting that reaches 100% of ad impressions and can be used with any Dstillery product. Our premier user segment product, Custom AI Audiences, is a just-for-your-brand targeting solution that refreshes hundreds of millions of users every 24 hours to deliver the best performance. About the team: Data Science is at the core of our offerings at Dstillery, and as a result all members of our Data Science team have the opportunity to make an impact on our company and the industry. The Data Science Research team leads the creation and development of new products to meet the ever changing needs of the digital advertising industry. We focus on building high performing products for our clients with integrity and transparency, and we have a commitment to the development of privacy friendly solutions. As a Data Scientist on the Data Science Research team you will play a critical role in bringing new products to market.  Role: - Prototype innovative ideas, conduct experiments, and iterate quickly to develop data-driven solutions for complex business challenges - Independently work on end-to-end research projects while actively collaborating with a team of data scientists - Present and promote results to internal stakeholders and external clients and partners. - Support and improve existing data science products - Analyze large, complex, and noisy datasets to extract actionable insights and support data-driven decision-making - Design, implement and evaluate machine learning and statistical methods to perform exploratory data analysis, data storytelling and product development  - Design and execute A/B tests and experiments to optimize product performance and maximize revenue growth - Pursue patents where applicable - Contribute to thought leadership in the community with presentations and publications   Qualifications: - Independent research experience is mandatory. A Ph.D. in a quantitative field (e.g. machine learning, statistics, physical science, or quantitative social science) is preferred, or a M.S. in Machine Learning or statistics with at least 3 years of independent research. - Experience using real data to solve real problems. - Expertise in statistical modeling, machine learning, and fluency in the related technical tools.  - Interest in applying machine learning to large datasets to solve business problems.  - Knowledge of current large language models and generative AI tools and an interest in applying them to data products. - Excellent oral and written communication skills; comfort in a client-facing role. - A track record in contributing to publications and/or presentations in a quantitative field. - Intermediate programming skills. - You should be ready to learn and work with Python, Google Cloud Platform, Scikit-learn, TensorFlow, PyTorch, Spark, BigQuery and SQL