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.
Required knowledge of:
- Python
- SQL
- Cloud Platforms (GCP, AWS, Azure)
- Data Warehouses (BigQuery, Snowflake, Redshift)
- LLMs / AI APIs
- Git / GitHub
Nice to have:
- 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:
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
Level 2 - Possesses developing capabilities
Level 3 - Possesses notable capabilities.
Level 4 - Possesses strong capabilities.
Level 5 - Possesses advanced capabilities.