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Job Responsibilities:

Collaborate with stakeholders across the organization to identify opportunities for data - driven solutions. Mine and analyze data from company databases to optimize processes and business strategies. Evaluate the effectiveness and accuracy of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to datasets. Utilize predictive modeling to enhance customer experiences, revenue generation, and other business outcomes. Establish and implement an A/B testing framework to assess model quality. Partner with functional teams to implement models and monitor their impact. Develop processes and tools to monitor model performance and data accuracy.

Qualifications:

Masters or PhD degree in Statistics, Mathematics, Computer Science, or a related quantitative field. 5-7 years of experience in data manipulation, statistical modeling, and data analysis. Strong problem-solving skills with a focus on product development. Proficiency in statistical computer languages (e.g., R, Python) for data manipulation and analysis. Experience in data architecture design and implementation. Comprehensive knowledge of machine learning techniques (e.g., clustering, decision tree learning, artificial neural networks) and their practical applications. Familiarity with advanced statistical concepts (e.g., regression, distribution properties, statistical tests). Excellent written and verbal communication skills for effective collaboration across teams. A passion for exploring new technologies and techniques.

Preferred Skills and Experience:

Coding knowledge and experience in multiple languages (e.g., C, C++, Java, Python). Expertise in statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees). Experience querying databases and using statistical computer languages (e.g., R, Python). Familiarity with web services. Experience developing and applying advanced machine learning algorithms (e.g., regression, simulation, modeling, clustering). Experience analyzing data from third-party providers (e.g., Google Analytics, Site Catalyst). Knowledge of distributed data/computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark). Experience working in a cloud platform Azure, GCP, AWS and their datawarehouse technologies BigQuery, Snyapse etc Knowledge/Experience with Snorkel AI is a strong plus