Machine Learning Scientist 5 – Forecasting Aggregation

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop, prototype, and refine supervised machine learning models that predict campaign delivery outcomes, such as delivery risk, reach, frequency, and contention.

• Analyze demand-side campaign results using supply-side indicators, including targeting, frequency caps, contention, and pacing.

• Create evaluation frameworks for both offline and online settings to assess accuracy, robustness, distribution shifts, and enhancements over the simulation baseline.

• Take ownership of feature engineering and contribute to the team’s feature store utilizing ad-serving logs, campaign characteristics, and supply signals.

• Guarantee model explainability and interpretability for stakeholders in sales and media planning.

• Collaborate with ML engineers to deploy models at scale while monitoring their health and drift.

• Work with product, engineering, and sales teams to define objectives, constraints, and trade-offs, promoting the adoption of ML-driven forecasts.

• Convey technical decisions, trade-offs, and findings to both technical and non-technical audiences.

⛳️ Requirements

• An advanced degree (PhD or Master's) in Statistics, Mathematics, Computer Science, or a related quantitative discipline.

• Over 5 years of relevant experience in building machine learning models on large-scale datasets.

• Profound expertise in supervised learning, particularly with gradient-boosted trees and regression techniques.

• Exceptional feature engineering abilities.

• Familiarity with feature stores and standard ML lifecycle practices, including versioning, evaluation, monitoring, and retraining.

• Demonstrated capability to prototype algorithms and rigorously validate them against production data.

• Strong programming proficiency in Python and robust SQL skills.

• Working knowledge of ad-serving and campaign concepts, such as targeting, frequency caps, contention, bidding, pacing, budget planning, and campaign objects and attributes.

• Comprehension of reach, frequency, impressions, clicks, and outcomes.

• Insight into both supply-side ad-serving rules and inventory behaviors, along with demand-side campaign attributes and advertiser objectives.

• Experience in advertising is highly preferred.

• Ability to work autonomously and drive project initiatives.

• Capable of clearly communicating technical and statistical concepts to diverse audiences.

• Experience with DSP, SSP, or publisher-side ad platforms is a plus.

• Familiarity with Metaflow or similar large-scale ML tools is advantageous.

• Experience collaborating with ML engineers to deploy and monitor production ML systems is beneficial.

• Experience in creating data products, dashboards, or explainability tools is a plus.

• Familiarity with applying GenAI to enhance developer or research productivity is an asset.

🏝️ Benefits

• Annual salary-only compensation structure with the option to choose between salary and stock options.

• Health Plans.

• Mental Health support.

• 401(k) Retirement Plan with employer match.

• Stock Option Program.

• Disability Programs.

• Health Savings and Flexible Spending Accounts.

• Family-forming benefits.

• Life and Serious Injury Benefits.

• Paid leave of absence programs.

• Flexible time off for full-time salaried employees.