[ The Impact You'll Be Contributing to Moloco ]
Product Data Science (PDS) is the global team of data scientists whose mission is to provide data-driven insights to improve decision-making and design, resulting in best-in-class Demand Side Platform (DSP) products and services. As a senior data scientist in PDS, you will derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system and provide a data-driven insight and scientific solution.

[ The Opportunity ]
• Data Analysis and Research: analyzing a large dataset with queries and scripts, extracting valuable signals from noise, and producing actionable insights into how we could complete and improve Moloco’s complex ML and bidding system.
• Simulation and Modeling: validating and quantifying the efficiency and performance gain from hypotheses through rigorous simulation and modeling.
• Experimentation and Causal Inference: developing a robust experiment design and metric framework and providing reliable and unbiased insights for product and business decision-making.

[ Minimum Requirements ]
• Bachelor’s degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).
• 3+ years of work experience in data science-related fields or an advanced degree such as a Master’s or Ph.D. in a quantitative discipline with 2+ years of experience
• Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets, and using statistics to arrive at a recommendation.
• Excellent verbal and written communication skills, with the ability to present information and analyze results effectively.
• Ability to build positive relationships within DSA and with our stakeholders and work effectively with cross-functional partners in a global company.
• Statistics: must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Machine Learning: must have a deep understanding of ML algorithms (i.e., deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and their development, validation, and evaluation.
• Programming: experience with Python, R, or other scripting languages, and database language (e.g., SQL) or data manipulation (e.g., Pandas, Dplyr) are required.

[ Preferred ]
• Advanced degree such as Master’s or PhD in a quantitative discipline.
• Ability to manage multiple projects at the same time while paying attention to detail and translating analysis results into business recommendations.
• Proven ability to own projects end-to-end, even when you have to get creative: you do more than complete delegated tasks.
• Demonstrated leadership and self-direction. Willingness to both teach others and learn new techniques.