The Walt Disney Company

Analyst

• Collaborate with the manager, senior manager and a variety of external data providers and internal teams, to execute research that directly attributes consumer sentiment or behavior to exposure to ads on Disney properties (including: Hulu, ABC, Freeform, ESPN, Disney Channel, etc.)
• Develop and market case studies, both internally and externally, that demonstrate the power of Disney’s measurement capabilities.
• Build reports for sellers to utilize with clients to help inform deals.
• Educate individual Disney Advertising Sales teams and on full funnel measurement solutions including methodology overview, navigating vendor dashboards and analyzing results

Analyst, Data Outcomes – Attribution

Marketing

• Assist with marketing strategies and go-to-market plan development to deliver our business goals
• Provide support with communication plan development across the team
• Evaluate campaign creatives and track approvals/status updates with agencies
• Apply data to make strategic recommendations and track program/product budgets
• Collaborate with teams to deliver assets, campaign pitch kits, toolkits, and content following brand guidelines and maintaining updates
• Provide generational knowledge into trends and ways of thinking
• Be an active participant and perform overall project management/ad hoc requests from leadership

Consumer Products Marketing Strategy Intern

Frontend Engineer

• Writing and reviewing a lot of code and tests
• Reviewing code and test implementations for best practices and algorithmic complexity
• Available to support engineers on an On-Call shift, when needed
• Reading requirements documentation from Product, providing a perspective on feasibility and translating into implementation tasks, and partnering with teams’ leads through execution as needed
• Exploring, researching, implementing proofs-of-concept, and proposing solutions that will improve Ad Serving systems (reduce cost and overhead, improve maintainability, minimize the time features take to be in production, etc)
• Defining, reviewing, and documenting software and system designs in a high throughput, low latency microservices environment
• Enhancing systems’ observability with proper metrics, monitors, and alerts
• Mentoring and inspiring others in all aspects of professional software development

Principal Front-end Engineer – Front-end, UI, Full Stack

Data Scientist

• Drive innovation and apply data science and statistical analysis in a variety of areas to enhance every aspect of advertising serving, including inventory forecasting, ad experience, ad pacing, pricing, targeting, advertising creation and enhancement, and efficient ad delivery
• Translate business questions into data science framework; develop data analysis and ML models for complex ad challenges with fast turnaround
• Develop rigorous evaluation pipelines for generative AI technologies, including visual generations (image, video) and/or LLM-based agentic generations
• Define and evaluate key metrics in various product areas
• Partner closely with generative AI specialists to support the creation of datasets for generative AI modeling applications
• Develop Standard Operating Procedures for human-driven evaluations or labeling
• Deliver data insights and provide data-driven recommendations to cross-team stakeholders
• Design and analyze A/B tests for machine learning algorithm iterations
• Establish strong partnership with stakeholders, including product managers, engineers and program managers, in a collaborative environment

Senior Data Scientist, Ads Research

Full-stack Engineer

• Lead & Develop High-Performing Teams: Recruit, onboard, mentor, and manage a team of Data Product Engineers, including Lead Engineers
• Strategic Data Product Leadership & Business Alignment: Lead the development and communication of our data product strategy and roadmap, actively collaborating with business leaders and stakeholders across all relevant departments
• Architectural Guidance & Technical Governance: Provide architectural oversight and technical guidance to your team, ensuring data product designs are scalable, resilient, secure, and maintainable
• Drive Operational Excellence: Establish and enforce robust processes for data product lifecycle management, including incident response, performance monitoring, cost optimization, and adherence to data governance policies
• Vendor & Resource Management: Manage budget allocation for your team, evaluate and manage relationships with external vendors and technology partners, ensuring optimal utilization of resources and technologies
• Innovate & Champion AI/ML Data Readiness: Guide the team in designing and building data products that specifically empower our AI/ML efforts

Manager, Data Product Engineering

• Lead the full lifecycle development of data products, including requirements gathering, architectural design, implementation, testing, and deployment
• Ensure data products are discoverable, well-documented, and adhere to strict data quality standards
• Apply a pragmatic combination of Domain-Driven Design (DDD) principles to deeply understand core business contexts and translate them into robust, Kimball-inspired dimensional models that power our data products within Snowflake
• Architect and implement highly efficient, event-driven data pipelines using AWS Kinesis for data ingestion and stream processing, leveraging AWS Lambda for serverless transformations and real-time data delivery
• Develop, optimize, and maintain complex SQL-based data transformations using dbt (Data Build Tool) within our Snowflake data platform, ensuring modularity, testability, and version control for all data models
• Collaborate closely with our AI/ML workbench to design and build data products specifically tailored for machine learning initiatives, including feature engineering, data preparation, and ensuring data readiness for model training and inference
• Establish and enforce best practices for data governance, metadata management, data lineage, and data observability to ensure the reliability and integrity of our data products.

Senior Data Product Engineer

Product Manager

• Define and communicate the strategic roadmap for Commerce & Finance data domains, ensuring alignment with business objectives and scalable value delivery.
• Identify, evaluate, and prioritize capitalizable data products and solutions that drive measurable business impact and can be leveraged across the organization.
• Serve as the subject matter expert for Commerce & Finance data domains, understanding data sources, structures, usage patterns, and their business impact.
• Proactively manage initiatives to ensure outcomes are achievable, realistic, and aligned with organizational priorities and data principles.
• Lead the definition and documentation of detailed data requirements for new and existing data products, collaborating with stakeholders to capture business needs and technical specifications.
• Oversee the end-to-end lifecycle of Commerce & Finance data products, including requirements gathering, data discovery, modeling, and documentation.
• Conduct hands-on technical activities such as data profiling, quality assessments, and the development of data rules (contracts, pseudo code).
• Establish and maintain ongoing data quality measurement processes to proactively identify, monitor, and resolve issues.
• Manage product-related issues, including root cause analysis and resolution, ensuring alignment with data governance and business priorities.
• Create and maintain comprehensive product documentation, including detailed data models and product-specific guidelines.
• Collaborate with business stakeholders in Commerce, Finance, and related domains to understand evolving needs and ensure data products drive measurable value.
• Drive user adoption by tracking engagement metrics, gathering feedback, and iterating on solutions for enhanced satisfaction and business impact.
• Foster trust and alignment with stakeholders, ensuring clear communication around expectations, timelines, and product outcomes.
• Partner with engineering, architecture, and analytics teams to deliver scalable, high-quality data solutions.
• Champion data governance, compliance, and scalability across all Commerce & Finance data solutions.
• Leverage industry best practices and cutting-edge data technologies to ensure robust, reliable, and compliant data products.
• Promote operational excellence and continuous improvement in data usability, performance, and quality.
• Advocate for agile methodologies and iterative delivery practices in data product development.