Responsibilities

• Perform analysis on large datasets and produce qualitative visualizations based on reporting requirements
• Develop analytical solutions and dashboards that integrate data from a wide variety of sources such as relational databases, AWS, data virtualization tools
• Understand technology operations data from many different sources in detail to create these models
• Optimize workflows and scripts on data lake for data cleaning, processing, and transformation
• Develop, prototype, and deploy machine learning models
• Extract and derive useful metrics and KPIs from raw data gathered from multiple data sources
• Collaborate with data engineers’ team to create, maintain, and enhance data ingestion pipelines which gather data from various systems or sources
• Partner closely with service managers and engineers to understand the underlying data and help them make business decisions through insights and data products

Minimum Qualifications

• Bachelors in Computer Science, Business Analytics, Data Science, Management of Information Systems, Engineering or other quantitative discipline
• Proficiency with data analysis using Python and experience with open source data science toolkits (Pandas, SciPy, SciKitLearn, NLTK)
• Familiarity with various statistical and machine learning techniques including classification, regression, dimension reduction, regularization, clustering and various multivariate methods
• Familiarity with relational data modeling and SQL
• Hands-on experience with modeling or hypothesis testing
• Readiness to learn and pick up new technologies such as AWS Sagemaker to build, train and deploy your models
• Excellent oral and visual communication skills
• Prior experience (2-3 years) working in a global, high technology company

Preferred Qualifications

• Adaptable and comfortable with complexity and uncertainty
• Be self-motivated, creative and collaborative
• Prior experience implementing and deploying data science models or data products in Production
• Experience working in an Agile/Scrum environment
• Experience working in an AWS environment and leveraging its offerings such as EC2, S3, Lambda, Glue, Athena, Sagemaker etc.