Senior Data Scientist

140,000 - 150,000 with equity

Hybrid Ann Arbor Michigan

My client is a prominent technology firm focused on advancing commerce media technology and providing strategic solutions for ad placements and digital marketplaces. Their platforms leverage first-party data to enhance ad personalization and boost revenue across a range of industries.

As a Senior Data Scientist, you will be pivotal in leveraging data-driven solutions to solve complex business challenges and drive actionable insights. Reporting directly to the Director of Data Science, you will collaborate closely with cross-functional teams. In this role, you will be at the forefront of developing and deploying advanced systems to analyze and optimize vast datasets. You will be responsible for designing scalable models and tools, utilizing machine learning and statistical methods to improve ad delivery and relevance.

Responsibilities:

• Develop and implement highly scalable classifiers and tools using machine learning, data regression, and rule-based models.
• Build and refine production-grade models on large-scale datasets to enhance ad performance and relevancy.
• Use data-driven insights to address key challenges such as cross-channel optimization and A/B testing.
• Collaborate with cross-functional teams, including marketing, product, and engineering, to drive data-driven solutions.
• Leverage large-scale data processing technologies like Spark and Hive, and machine learning platforms to handle complex datasets.

Requirements:

• MUST be coming from an ad tech background
• ad auctioning and bidding is a MUST
• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field; Master’s or Ph.D. preferred.
• Experience in machine learning engineering or related roles, with a track record of developing and deploying models in production environments.
• Proficiency in Python for development and debugging, familiarity with GoLang, Perl, and TensorFlow.
• Experience with model deployment tools like Airflow, Databricks, AWS, Docker.
• Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with cloud computing platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving skills with attention to detail, effective communication, and collaboration skills across technical and non-technical teams.
• Experience in Agile/Scrum methodologies and interdisciplinary team environments is a plus.

BENEFITS

As a Machine Learning Engineer, you can expect to earn anywhere from $140,000 -150,000 (depending on experience) and highly competitive benefits including equity.

HOW TO APPLY

Please register your interest by sending your Resume to Cassie Wandell via the Apply link on this page

KEYWORDS

Machine Learning | Infrastructure | AI | Python | SQL | Software Engineering| Deep Learning | Pytorch | Tensorflow