Data Scientist III

OpenX is focused on unleashing the full economic potential of digital media companies by creating digital advertising markets and technologies that deliver optimal value to publishers and advertisers across all screens. The company has a team experienced in designing and operating high-scale ad marketplaces, applying market design, technical innovation, operational excellence, and empathetic partner service to digital advertising.

• B.S. or M.S. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations Research, or related field with 5+ years of relevant industry experience; or Ph.D. with 2+ years of relevant experience.
• Proven ability to independently own the full data science lifecycle from problem formulation to model deployment and maintenance.
• Solid expertise in machine learning and statistics methods including gradient-boosted models, deep neural networks, time series, causal inference, and experimentation design.
• Strong foundation in probability and statistics with techniques scalable to large datasets.
• Experience designing and analyzing experiments and building robust validation frameworks.
• Proficient in Python and SQL; experience with ML frameworks such as TensorFlow or PyTorch.
• Ability to write efficient, modular, well-tested code and collaborate with engineering to deploy models.
• Strong communication skills to convey complex technical concepts to diverse audiences.

Desired:

• Experience with RTB environment models or bidding algorithms.
• Experience with cloud platforms, especially GCP and Vertex AI.
• Familiarity with ML pipeline and orchestration tools like TFX, Kubeflow, or Airflow.
• Knowledge of additional programming languages such as Java and Go.
• Experience in digital media, marketing technology, or advertising technology, particularly marketplace or exchange systems.
• Experience supporting and improving production ML models.
• Experience mentoring junior data scientists.

• Own the end-to-end data science lifecycle for moderately complex models and significant project components, including data ingestion, feature engineering, modeling, validation, deployment, monitoring, and retraining.
• Apply expertise in machine learning and statistics methods such as gradient-boosted models, deep neural networks, time series, causal inference, and experimentation design.
• Write efficient, modular, well-tested code for data processing, feature engineering, and model training/inference using distributed tools like Vertex AI pipelines, Dataflow, and BigQuery.
• Design and implement robust validation frameworks for experiments and models, accounting for biases and real-world performance.
• Troubleshoot complex model performance issues, data anomalies, and code bugs with minimal guidance.
• Define analytical approaches and scope data science projects for moderately complex or ambiguous business problems.
• Partner with product managers and stakeholders to define success metrics and translate marketplace problems into data science solutions.
• Lead design and analysis of experiments (e.g., A/B tests, switchback) and interpret complex model and experimental results.
• Identify opportunities where data science can add value and initiate exploration.
• Follow and improve team processes for coding standards, documentation, reproducibility, and experimentation.
• Mentor junior data scientists, provide technical guidance, review code and analyses, and support their skill growth.
• Influence technical decisions on modeling, validation, and tooling within the team.
• Drive improvements to team standards, best practices, and analytical rigor; take ownership of specific team practices or components.
• Educate stakeholders on data science model capabilities and limitations, explaining complex methodologies to technical and non-technical audiences.
• Participate actively in recruiting and provide interview feedback for candidates.

OpenX is committed to equal employment opportunities and does not discriminate against employees or applicants on any legally-recognized basis including age, race, creed, color, religion, national origin, sexual orientation, sex, disability, genetic information, military or veteran status, marital status, gender identity, pregnancy, childbirth or related medical condition, and other protected characteristics as established by law.