The Consumer Data Science team at Client leverages data to help grow client through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of metrics, measurement, modeling, and experimentation. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what''s possible with machine learning and statistical modeling. About the Role: We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Consumer Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to help grow Client. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Client. Main job duties include: Design, develop, and apply DS solutions to inform improvements in across our main Consumer product teams, including Feeds, Search, Growth and Content Ecosystem. Creating data assets (new tables, self-serve dashboards, etc.) to enable partners to answer their own data questions Creating reporting dashboards for product and engineering partners to understand topline metrics movements and deep dive into specific areas of interest Analyze large-scale datasets to identify trends, patterns, and insights. Collaborate with product managers and engineers to define product requirements and translate them into data science solutions Uncovering strategic insights and sharing them with stakeholders to shape future product directions Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition Communicate findings and recommendations to stakeholders across the organization Qualifications: BS, MS or PhD in Computer Science, Statistics, Mathematics, or a related field 3+ years of experience in data science, machine learning, or a related field Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus Experience with SQL and relational databases Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch Bonus Points: Experience working in the Consumer technology space Experience with causal inference and A/B testing:
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