Viant

Applied Scientist

Viant • $130K — $170K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1-3 years of experience in developing and applying machine learning models in production or research environments.
  • Strong foundation in machine learning, deep learning, probability, statistics, and optimization, with practical experience in Python and frameworks like PyTorch or TensorFlow.
  • Experience with reinforcement learning, contextual bandits, and sequential decision-making methods through coursework, research, or projects.
  • Ability to precisely formulate machine learning problems, including objectives, labels, and evaluation metrics.
  • Experience analyzing large-scale data and effectively communicating technical findings to diverse teams.
  • Interest in building models that enhance real-world decision-making in production systems.
  • Familiarity with reinforcement learning applications in advertising, marketplaces, or recommendation systems.

Responsibilities

  • Develop, train, and evaluate models for ad optimization and targeting using reinforcement learning and contextual bandits.
  • Study auction dynamics and feedback mechanisms to enhance real-time advertising decisions.
  • Translate research concepts into production-ready models for high throughput and low latency environments.
  • Design and analyze experiments to measure model quality and business impact.
  • Collaborate with engineers to deploy and improve models in production, addressing data-related challenges.
  • Apply quantitative reasoning to problems involving click-through rates and return on ad spend.
  • Contribute to a research-oriented team culture through technical communication and knowledge sharing.

Benefits

  • Fully paid health insurance.
  • Paid parental leave.
  • Unlimited PTO.
  • Investment in professional growth and employee well-being.
Full Job Description
WHAT YOU'LL DO

Viant's Machine Learning team is building autonomous advertising systems that make real-time decisions across targeting, ad optimization, bidding, measurement, and personalization. These systems process hundreds of millions of events daily and operate in the high-throughput, low-latency environment of programmatic advertising.

As an Applied Scientist, you will apply reinforcement learning and related decision-making methods to improve how Viant selects, ranks, and bids on advertising opportunities. You will work across contextual bandits, exploration and exploitation, counterfactual learning, and model-based experimentation to turn research into production systems that improve campaign performance, auction efficiency, and measurable business outcomes.
THE DAY-TO-DAY
  • Develop, train, and evaluate reinforcement learning, contextual bandit, ranking, and prediction models for ad optimization, bid optimization, targeting, and personalization.
  • Study auction dynamics, delayed feedback, exploration and exploitation, budget constraints, pacing, and reward design to improve real-time advertising decisions.
  • Translate research ideas into production-ready models that operate reliably at high throughput and low latency across Viant's advertising platform.
  • Design and analyze offline and online experiments, including counterfactual and off-policy evaluation where appropriate, to measure model quality and incremental business impact.
  • Partner with engineers to deploy, monitor, retrain, and improve models in production, addressing issues such as data leakage, class imbalance, drift, calibration, and changing market conditions.
  • Apply quantitative reasoning and statistical modeling to problems involving click-through rate, conversion, return on ad spend, targeting, attribution, identity, and measurement.
  • Collaborate with scientists, engineers, and product partners to define objectives, labels, loss functions, reward signals, evaluation metrics, and practical delivery plans.
  • Contribute to a rigorous, research-oriented team culture through technical communication, code and model reviews, experimentation, and knowledge sharing.
MUST HAVE
  • 1-3 years of experience developing and applying machine learning models, ideally in production or research environments with measurable outcomes.
  • Strong foundation in machine learning, deep learning, probability, statistics, and optimization, with practical experience using Python and frameworks such as PyTorch or TensorFlow.
  • Coursework, research, internship, or project experience with reinforcement learning, contextual bandits, sequential decision-making, recommendation systems, online experimentation, or related methods.
  • Ability to formulate a machine learning problem precisely, including objectives, labels, features, loss or reward functions, evaluation metrics, and experimental design.
  • Experience analyzing large-scale data and communicating technical findings clearly to scientists, engineers, and cross-functional partners.
  • Interest in building models that move beyond offline accuracy and improve real-world decisions in production systems.
  • Experience with reinforcement learning in advertising, marketplaces, recommendation systems, robotics, games, or other sequential decision-making environments.
  • Exposure to contextual bandits, off-policy or counterfactual evaluation, causal inference, auction theory, or online experimentation.
GREAT TO HAVE
  • Experience with digital advertising, real-time bidding, audience modeling, ad ranking, personalization, or large-scale recommendation systems is a plus.
  • Experience with distributed computing, cloud platforms, LLMs, generative AI, or multimodal AI is also welcome, but the core focus of this role is production-oriented reinforcement learning and decisioning.


LIFE AT VIANT

Investing in our employee's professional growth is important to us, but so is investing in their well-being. That's why Viant was voted one of the best places to work and some of our favorite employee benefits include fully paid health insurance, paid parental leave and unlimited PTO and more.

Base compensation range: $130,000 - $170,000

In accordance with California law, the range provided is Viant's reasonable estimate of the compensation for this role. Final title and compensation for the position will be based on several factors including work experience and education.

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About Viant

Viant is a marketing consulting firm that provides data-driven solutions for brands and agencies. The company was founded in 1999 by Tim Vanderhook and Chris Vanderhook and is headquartered in Los Angeles, California. Viant's services include audience targeting, programmatic advertising, and measurement and analytics. The company has been recognized as one of the fastest-growing private companies in America by Inc. Magazine and has won numerous awards for its work, including Cannes Lions and Effies.
Learn more about Viant
Size
100 employees
Market Cap
$228.7 million
Industry
Net Income
$13.1 million
Revenue
$160.7 million
NASDAQ

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