Expert Data Analyst

Data Scientist Role OverviewWe are seeking an accomplished Data Scientist to join our advertising technology division. As a key member of the team, you will play a pivotal role in designing and implementing machine learning models that drive ad delivery efficiency and maximize campaign outcomes.The ideal candidate will have extensive experience in data analysis and machine learning using Python and SQL, with a strong foundation in statistics, probability, and experimental design. They should be proficient in libraries such as Pandas, NumPy, scikit-learn, and visualization tools, with hands-on experience in large-scale data processing and reproducible analytics workflows.The successful Data Scientist will work closely with product, engineering, and operations teams to translate business requirements into actionable data solutions. They will define optimization problems for ad delivery, establish KPIs, metrics, and monitoring dashboards, and perform data preprocessing, feature engineering, and model development for tasks such as price optimization, CTR/CVR prediction, and creative performance analysis.In this role, you will have the opportunity to work on cutting-edge technologies for high-traffic, low-latency systems and big data processing. You will be responsible for end-to-end ownership of projects, from hypothesis formulation and feature engineering to deployment and continuous improvement in production environments.Key Responsibilities:Define Optimization Problems: Develop data-driven solutions that optimize ad performance, enhance audience targeting, and enable seamless campaign execution across multiple channels.Perform Data Preprocessing and Feature Engineering: Use your expertise in data analysis and machine learning to develop robust evaluation strategies and deploy ML models in production environments.Collaborate with Cross-Functional Teams: Work closely with product, engineering, and operations teams to translate business requirements into actionable data solutions.Implement MLOps Practices: Establish training/inference pipelines, drift detection, automated rollback, and governance for quality and privacy.Technical Environment:Cloud-Based Infrastructure: Experience with cloud-based infrastructure, such as GCP or equivalent.Big Data Tools: Proficiency with BigQuery, Dataflow, Pub/Sub, and other big data tools.Distributed Systems and Real-Time Processing: Hands-on experience with distributed systems and real-time processing.Programming Languages: Expertise in Python and Go programming languages.Infrastructure Automation: Familiarity with Terraform and Ansible automation tools.Mandatory Qualifications:3+ Years of Experience: Minimum 3 years of experience in data analysis and machine learning using Python and SQL.Statistics and Probability: Strong foundation in statistics, probability, and experimental design.Libraries and Tools: Proficiency in libraries such as Pandas, NumPy, scikit-learn, and visualization tools.Large-Scale Data Processing: Hands-on experience in large-scale data processing and reproducible analytics workflows.ML Model Deployment: Experience in deploying ML models in production environments.Preferred Qualifications:Advanced Optimization Techniques: Experience with advanced optimization techniques, such as Bayesian optimization and multi-armed bandits.Creative Optimization: Familiarity with creative optimization and generative AI for ad content.Real-Time Streaming Platforms: Experience with real-time streaming platforms, such as Kafka and Flink.