Machine Learning Engineer

About the Role: We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health. You will play a crucial part in delivering actionable insights and solutions to our clients, and your work will be integral to our mission.

Responsibilities include but are not limited to;

• ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health.
• Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization.
• Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training.
• Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement.
• Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs.
• Collaboration: Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless integration of data science solutions into our products.
• Research and Innovation: Stay up-to-date with the latest developments in the field of data science and machine learning, and explore innovative approaches to problem-solving.

Requirements

• Master's or Ph.D. in a related field with a strong academic background.
• Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models.
• Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning.
• Proficiency in data manipulation, feature engineering, and model evaluation.
• Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn.
• Excellent communication skills and the ability to collaborate effectively within cross-functional teams.
• A passion for continuous learning and staying updated with the latest trends and technologies in data science.
• Strong problem-solving abilities and the capacity to translate complex data into actionable insights.

• Python
• SQL
• Cloud Platforms (GCP, AWS, Azure)
• Data Warehouses (BigQuery, Snowflake, Redshift)
• LLMs / AI APIs
• Git / GitHub

• Data Transformation (dbt)
• Semantic Layers (Cube, Looker, dbt Metrics)
• TypeScript
• Bayesian modeling experience - ideally Marketing Mix Models (PyMC, Stan, or similar..). Understands priors, MCMC sampling, posterior diagnostics.
• Causal inference / experimentation- geo experiments (matched markets), A/B testing at scale. Familiar with incrementality measurement.
• Marketing/advertising domain- understanding of attribution, media channels (paid social, search, display, video), campaign structures.
• Nice to have - familiarity with adstock/saturation curves and budget optimization

Our interview process includes, but is not limited to the following:

• Excel and Typing Test

We offer a competitive salary and benefits based on ability level, including:

• Unlimited vacation policy
• Monthly Phone Stipend
• Comprehensive Medical, Dental, and Vision insurance options
• 401(K) plan with matching
• Dog friendly office
• Hybrid work opportunity
• Professional Development Program
• Bonus Perk - Seamless allowance

Total compensation based on education, experience, and skills level ($90,900-$254,100)

• Level 1 - Possesses essential capabilities

  • $90,900-$123,540

• Level 2 - Possesses developing capabilities

  • $123,540-$156,180

• Level 3 - Possesses notable capabilities.

  • $156,180-$188,820

• Level 4 - Possesses strong capabilities.

  • $188,820-$221,460

• Level 5 - Possesses advanced capabilities.

  • $221,460-$254,100