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
- 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 ability to translate complex data into actionable insights.
Required Knowledge
- 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), understanding priors, MCMC sampling, posterior diagnostics.
- Causal inference/experimentation - geo experiments (matched markets), A/B testing at scale, familiarity with incrementality measurement.
- Marketing/advertising domain understanding of attribution, media channels (paid social, search, display, video), campaign structures.
- Familiarity with adstock/saturation curves and budget optimization.
Benefits
- 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.
- Level1 - Possesses essential capabilities: $90,900-$123,540
- Level2 - Possesses developing capabilities: $123,540-$156,180
- Level3 - Possesses notable capabilities: $156,180-$188,820
- Level4 - Possesses strong capabilities: $188,820-$221,460
- Level5 - Possesses advanced capabilities: $221,460-$254,100
Locations
- NewYork City: nd St, Suite602, Queens, NY11101, United States
- Bogotá: WeWork Av. Carrera Usaquén, Piso10, Bogotá, Distrito Capital de Bogotá 110111, Colombia
- MexicoCity: Av. Insurgentes Sur1082, Piso2, Oficina2008, Ciudad de México, CDMX03100, México