Staff Data Scientist - BLR

About Us

Aarki is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our comprehensive audience engagement platform includes creative strategy and execution. With over 14 years in the industry, we handle 5M mobile ad requests per second from over 10B devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.

Role Overview

We are looking for a passionate and experienced Staff Data Scientist to join our innovative team. In this role, you will focus on the development and deployment of cutting-edge machine learning models, optimizing our programmatic demand-side platform (DSP). You will collaborate closely with other technical experts, contributing to technical solutions and strategic initiatives, all while driving advancements in machine learning and AI. 

If you have a strong track record of building production-grade solutions and are eager to push the boundaries of AI and mobile advertising, we want to hear from you! We offer a competitive salary, comprehensive benefits, and significant opportunities for career advancement.

Role & Responsibilities

• Design, develop, and implement advanced machine learning algorithms and data pipelines at scale for optimizing programmatic advertising, including user response prediction, bid landscape forecasting, fraud detection, and budget pacing strategies.
• Conduct applied research and leverage findings to enhance our platform’s performance and address complex business challenges.
• Develop and maintain a framework for performance evaluation and iterative development to ensure continuous improvement and innovation.
• Contribute to the development of technical solutions and collaborate with cross-functional teams to ensure alignment with business goals and KPIs.
• Collaborate with product, engineering, and business stakeholders to integrate machine learning models into production systems and applications.
• Focus on driving innovation, ensuring that machine learning models meet business objectives and exceed performance expectations.

Skills & Experience

• Minimum of 7 years in data science, with a proven track record of delivering end-to-end, production-grade machine learning solutions across domains such as deep learning, recommender systems, optimization algorithms, and Bayesian inference.
• Expertise in Python and experience with libraries like TensorFlow/PyTorch, Scikit-Learn, XGBoost, Spark, and SQL.
• Experience with deploying machine learning models to production systems.
• Strong problem-solving skills, with a deep understanding of probability, statistics, numerical optimization, and stochastic methods.
• Familiarity with real-time bidding (RTB), auction theory, and high-throughput, low-latency environments is a plus.
• Experience with additional programming languages (Rust, C++, C#, Java, or Scala) and large-scale data processing systems is a plus.
• Bachelor's in Mathematics, Physics, Computer Science, or a related technical field. Master’s or Ph.D. preferred.