Senior Data Scientist role focused on Yield Optimization at Verve. Responsibilities include leading design and development of large-scale data science systems and models, driving technical excellence in Demand Shaping, Floor Optimization, and Bid Optimization, identifying new technologies, managing large-scale initiatives, resolving complex technical problems, designing scalable systems for data processing and real-time model serving, evaluating architectural trade-offs, mentoring team members, refining problem-solving tools and documentation, partnering with Product Management and Backend Engineering, and maintaining hands-on contribution with model development, statistical analysis, and A/B testing. Requirements include 5+ years in Data Science or Machine Learning, AdTech industry expertise, mastery of Python and SQL, expertise in ML frameworks (TensorFlow, PyTorch, Scikit-learn), experience with Big Data and Cloud infrastructure (PySpark, Google Cloud Vertex AI), ability to design large-scale distributed systems and real-time ML pipelines, strong communication skills, ability to align teams on technical vision, and an advanced quantitative degree (Master's or PhD preferred).
What you'll do
Lead the design and development of large-scale, complex data science systems and models.
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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).
Tech stack
PythonSQLTensorFlowPyTorchScikit-learnPySparkGoogle Cloud Vertex AI
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