Sr Data Scientist (IC4) - Yield Optimization

Responsibilities

• Lead the design and development of large-scale, complex data science systems and models.
• Drive technical excellence across the Yield Optimization portfolio, including Demand Shaping, Floor Optimization, and Bid Optimization.
• Identify and champion new technologies or methodologies to maintain Verve's competitive edge in yield optimization.
• Plan and execute large-scale initiatives with significant impact, managing multiple interdependencies and cross-team collaborations.
• Resolve highly complex technical problems independently, often designing custom solutions.
• Design maintainable, scalable, and efficient systems for large-scale data processing and real-time model serving.
• Evaluate architectural trade-offs based on long-term business needs and technical debt considerations.
• Act as a technical leader and mentor to other data scientists and engineers across distributed teams.
• Refine team problem-solving tools, methodologies, and technical documentation to uplift the overall team competency.
• Partner closely with Product Management and Backend Engineering to align long-term technical roadmaps with business strategy.
• Maintain a high level of hands-on contribution, developing critical model components, conducting advanced statistical analysis, and designing robust A/B tests.

Required Skills

• Minimum of 5 years of experience in Data Science or Machine Learning, with a proven track record of delivering high-impact projects.
• Extensive AdTech industry expertise, with deep knowledge of programmatic auctions, supply/demand matching, and real-time bidding optimization.
• Master-level proficiency in Python and SQL.
• Deep expertise in ML frameworks (TensorFlow, PyTorch, or Scikit-learn) and their application at scale.
• Strong experience with Big Data and Cloud infrastructure (PySpark, Google Cloud Vertex AI, or equivalent).
• Proven ability to design and oversee the implementation of large-scale distributed systems and real-time ML pipelines.
• Exceptional communication skills with the ability to influence technical and non-technical stakeholders across the organization.
• Ability to navigate and align multiple teams around long-term technical visions and architectural standards.
• Advanced degree (Master's or PhD preferred) in a quantitative field (Applied Mathematics, Statistics, Computer Science, or Physics).