Simulmedia

• Design and build batch data pipelines that ingest, validate and transform multi-billion-row datasets • Model complex real-world data and evolve those models safely • Develop and operate workloads on lakehouse platform and data warehouse • Orchestrate pipelines with Airflow • Prove correctness and investigate data discrepancies • Build and maintain Python services and REST APIs • Optimize for performance and cost • Monitor production pipelines and participate in incident triage • Collaborate cross-functionally with product managers, data scientists, and stakeholders

• Design, build, and maintain backend services in Ruby (Roda) operating within a large-scale distributed microservice architecture. • Contribute to backend-focused TypeScript/Node.js work, including API design and tRPC procedures, in support of Next.js applications. • Own service reliability: instrumentation, monitoring, and observability across services (tracing, metrics, structured logging). • Collaborate closely with data engineers on data pipelines, ETL processes, and ensuring clean, well-modeled data flows between services. • Investigate and resolve production incidents; contribute to and follow oncall/runbook practices. • Design and evolve APIs with strong attention to authentication, authorization, and security best practices. • Participate in code reviews, pair programming, and knowledge-sharing sessions to ensure high-quality, maintainable code. • Write thorough unit and integration tests for backend services. • Work independently while communicating clearly across a distributed, cross-functional team.

• Develop and maintain supervised machine learning models to support ad targeting, measurement, and campaign optimization. • Perform data analysis, data validation, and feature engineering on large and complex datasets. • Collaborate with product, engineering, and analytics teams to translate business needs into data science solutions. • Evaluate model performance using appropriate metrics and iterate on model improvements. • Support optimization and experimentation efforts related to advertising performance. • Assist with deploying models to production in collaboration with engineering teams. • Monitor model performance and help troubleshoot issues in production. • Communicate results, insights, and limitations to both technical and non-technical stakeholders. • Stay up to date with industry best practices in data science and machine learning.

• Design and implement insights and analytics dashboards for the CTV self-service platform, providing users with actionable data to enhance their campaigns. • Develop both frontend (70%) and backend (30%) services using React, Next.js, and TypeScript, ensuring seamless integration between components. • Build robust, scalable APIs using tRPC to serve analytics data to the frontend application. • Create efficient pages using server-side rendering (SSR) or static site generation (SSG) via Next.js for performance-optimized analytics displays. • Collaborate with designers to implement responsive and visually appealing user interfaces using Tailwind CSS, ensuring a smooth, intuitive experience for the platform’s users. • Optimize the full stack to ensure quick load times, low-latency data fetching, and smooth user experiences, especially for data-heavy visualizations and analytics pages. • Deploy and manage the platform using Vercel, taking advantage of its serverless functions for backend processes and ensuring efficient deployments and scaling. • Participate in code reviews, pair programming, and knowledge-sharing sessions to ensure high-quality, maintainable code. • Implement unit and end-to-end testing for both frontend and backend components to ensure reliability and reduce bugs in production.