What You'll be doing:

• Locate, extract, manipulate, and organize data from operational source systems in support of analytic tool development (SQL, Python, Linux and Ansible)
• Create and manage SQL Server entities for use in Data Science modeling and reporting
• Proficient usage of SQL data sources and database management like Hadoop, Oracle, and SQL servers
• Partner with varying levels of operations and resource management leadership to understand challenges, goals, and pain points, designing analytic solutions to address them
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Help develop and maintain code standards and repositories

Requirements:

• 5 - 10 years' building and optimizing ‘big data’ data pipelines, architectures and data sets
• Strong SQL expertise
• Experience working with Python and Linux.
• Experience working with AWS and Databricks.
• Understanding and experience with Natural Language Processing concepts including sentiment analysis, lexicon design, text summarization, aspect mining, topic modeling, etc.
• Understanding and experience with leading supervised and unsupervised machine learning methods such as Multiple Regression, Logistic Regression, Neural Networks, Deep Learning, KNN, Naive Bayes, SVM, Decision Trees, Random Forest, Gradient Boosting, and Ensemble methods
• Experience with Git (or equivalent)
• Solution design and troubleshooting skills
• Ability to extrapolate data into information to drive process improvements
• Ability to quickly learn how to use new software applications
• Comfortable working in projects with varying levels of ambiguity, complexity, uncertainty, and change