Staff Applied Scientist, Deep Learning Forecasting

About the role

Applied Scientists at TTD work closely with engineering throughout the lifecycle of the product, from ideation to productionalization and monitoring. Our data scientists are end-to-end owners. You will participate actively in all aspects of designing, researching, building, and delivering data-focused products for our clients and traders.

Responsibilities

• Develop ML/deep learning based models end-to-end to support various forecasting need throughout advertising campaign life cycle, including working on signal collection, feature construction, model evaluation and monitoring;
• Collaborate with engineer team on signal collection pipeline and model training, deployment and monitoring processes;
• Collaborate with downstream team to understand their forecasting needs and design appropriate models;
• Design offline and online model success metrics and use data to drive iterative model improvement.

Requirements

• Proficient in machine learning (ML) and deep learning (DL).
• You have a strong passion for enhancing and expanding your technical skills.
• Your expertise includes hands-on development of ML and DL solutions utilizing open-source tools and cloud computing platforms.
• Has a deep understanding of the foundations of statistics and ML/DL models.
• Hands-on experience building deep learning models at large scale.
• A track record of partnership with a cross-functional team of data scientists, engineers and product managers to deliver AI-powered analytics or models.
• Familiar with forecasting domain with solid knowledge background and application experience.
• Knowledge in privacy safe measurement and data storage is a plus.
• Possessing a keen sense of data intuition and the ability to innovate in the field of model development.
• Have a data driven mindset and use data to drive your model development plan.

Qualifications

• BS/MS with 8+ years or a PhD with 6+ years of experience working in a DS or ML role that involves bringing products from ideation to production.
• Experience in deep learning, PyTorch/ TensorFlow preferred.
• The ability to communicate with diverse stakeholders, making architecture recommendations, ensuring effective execution, and measuring quality of outcomes.
• Experience running heavy workloads on a distributed computing cluster (especially EMR or Databricks), leveraging technologies like Spark to work with large datasets preferred.
• Proficient in Python. Strong spark skills are a plus.

Skills

• Machine Learning
• Deep Learning
• Data Science
• Forecasting
• Signal Collection
• Feature Construction
• Model Evaluation
• Monitoring
• Cloud Computing
• Open Source Tools
• Large Scale Model Development
• Data Driven Approach
• Communication Skills
• Architecture Recommendations
• Quality Measurement
• Distributed Computing
• Spark Technologies
• Python Programming
• Spark Skills

Benefits

• Comprehensive Healthcare (Medical, Dental, Vision)
• Retirement Benefits (401k Plan, Company Match)
• Short and Long-Term Disability Coverage
• Basic Life Insurance
• Well-Being Benefits
• Tuition Reimbursement
• Parental Leave
• Sick Time (1 hour per 30 hours worked)
• Vacation Time (120 hours in the first year, 160 hours thereafter)
• Around 13 Paid Holidays Per Year
• Employee Stock Purchase Plan