What you;ll do-:

• Collaborate with stakeholders across the organization to explore ways to use company data to create business solutions.
• To optimize and improve product development, marketing approaches, and commercial strategies, data from company databases are mined and analyzed.
• Examine the efficacy and precision of new data sources and data collection procedures.
• To apply to data sets, create bespoke data models and algorithms.
• Increase and optimize customer experiences, revenue creation, ad targeting, and other company results via predictive modeling.
• Develop an A/B testing framework for the organization and evaluate model quality.
• To implement models and track outcomes, collaborate with various functional teams.
• Develop monitoring and analysis methods and tools for model performance and data

What makes you a great Fit-:

• Strong problem-solving abilities, focusing on product creation.
• Experience manipulating data and extracting insights from huge data sets using statistical computer
• languages (R, Python, SLQ, etc.).
• Working with and designing data architectures is a plus.
• Understanding of a variety of machine learning approaches (clustering, decision tree learning,artificial neural networks, and so on) as well as their real-world benefits and limitations.
• Advanced statistical techniques and ideas (regression, characteristics of distributions, statisticaltests, suitable application, etc.), as well as application experience, are required.
• Coding skills and experience in a variety of languages, including C, C++, Java, JavaScript, and others.
• GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, and other statistical and data mining approaches.
• Experience with databases and statistical programming languages such as R, Python, SLQ, and others.
• Redshift, S3, Spark, DigitalOcean, and other web services experience
• Regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, and other sophisticated machine learning methods and statistics
• Experience analyzing data from third-party sources such as Google Analytics, and Adwords, among