Senior Data Scientist

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

Requirements

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)