Machine Learning Engineer

• 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.

• 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

• Excel and Typing Test

WITHIN is the world's first Performance Branding company, partnering with some of the biggest brands in the world to drive business growth through innovative marketing strategies. Our integrated operating model collapses the traditional marketing silos between creative and media, performance and brand, and across media channels. With a full suite of offerings including media, creative, SEO, Lifecycle, Retail Media, Affiliate and Influencer, we’re able to work with our brand partners in an integrated fashion, allowing us to align marketing strategies back to core business objectives. Client teams at WITHIN are trained on how to always act as a trusted business partner, acting as a fiduciary to client needs above our own.

Teams at WITHIN have the ability to work with iconic brands such as The North Face, Timberland, Ben and Jerry's and Jose Cuervo. Everyone at WITHIN wants to grow and be challenged. It’s a collaborative place made up of small, closely knit and versatile teams that are fast and adaptive to solve problems and build systems.

Check out some of our work!

We weave AI into everything we do, using the latest tech across all teams to innovate, work smarter, and make better decisions. Whether it’s in creative, operations, or anything else, AI helps us level up and do things at a whole new scale. We expect our people to use AI in their daily work, fully embracing it as a critical tool to help us succeed. 

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