Data Science Machine Learning

Job Description The company aims to revolutionize the internet advertising market by leveraging state-of-the-art technology. Operating at the forefront of digital marketing, the company drives effective ad delivery through advanced data analysis and algorithm development, directly supporting the business growth of its clients. ■Responsibilities 1. Algorithm Development & Implementation - Price Floor Optimization: Participating directly in developing and improving automated price floor optimization logic. - Predictive Modeling: Building, deploying, and refining high-precision CTR (Click-Through Rate) and CVR (Conversion Rate) prediction models. - Targeting & RTB Enhancement: Designing and implementing algorithms to enhance targeting precision and optimizing Real-Time Bidding (RTB) logic (including bid optimization, pacing, and inventory allocation). - Experimentation: Designing and executing A/B tests alongside delivering comprehensive post-experiment validation reports. 2. Statistical Analysis & Modeling - Decomposition Analysis: Conducting detailed eCPM decomposition analyses (Fill Rate×Win Rate×Bid Rate). - Market Landscape Modeling: Visualizing and analyzing bid landscapes and modeling price elasticity. - Causal Inference: Applying causal inference techniques to accurately measure the business impact of platform features and policies. - Cross-Functional Communication: Translating complex analytical findings into actionable insights for Product Managers, Engineers, and Business stakeholders. 3. Team Management (Applicable to the Manager track) - People Management: Overseeing a team of data scientists, including goal setting, conducting 1-on-1 sessions, and performance evaluations. - Talent Development: Designing and executing strategic initiatives to upskill team members and foster technical excellence. - Cross-Department Collaboration: Driving day-to-day collaborative alignment between product, engineering, and business development units. - Stakeholder Reporting: Reporting progress and pitching high-level technical proposals directly to department heads and the executive leadership team. ■Team Structure - Data Science Team: 8 members ■Work Style - The team primarily operates on an in-office schedule, with the flexibility to work from home up to 2 days per week. ■Job Requirements Required: - 2+ years of experience implementing ML (Machine Learning). - Implementation experience in any of the following: Bid optimization, floor price optimization, pacing algorithms, CTR/CVR prediction models, targeting accuracy, recommendation systems, or demand forecasting. - Statistical analysis and modeling skills; experience solving business problems using statistical methods. - Experience explaining analytical results clearly to engineers and business stakeholders. - 1+ years of team lead or management experience (or experience as a Tech Lead). - Japanese Level: Business Level (JLPT N2 or higher). Preferred: - Proven track record in delivery, pricing, and demand optimization at ad tech companies (SSP/DSP). - Experience applying generative AI and LLMs to ad delivery. - Hands-on implementation skills in Python, SQL, Spark, Flink.