Data Scientist

Job Title: Data Scientist II Location: Remote Duration: 6 Months Contract on W2 (Possible extension) The Data Science role is critical to support for eDiscovery & Information Governance teams by addressing the growing volume and complexity of work. The perfect candidate will have a background in a quantitative or technical field, a perfectionist mentality, and will have excellent communication skills. You are focused on accuracy, a self-starter, and have demonstrated success in using analytics to drive understanding and to influence business decisions. Top 3 must-have HARD skills: • 3+ years’ experience doing quantitative analysis • Bachelor’s degree in a Quantitative or Technical field • SQL, Excel, and data analysis experience • Python/R scripting experience • Experience with distributed computing (Hive/Hadoop) • Experience with Unix/Linux • Experience initiating and driving projects to completion with minimal guidance • Experience working cross-functionally and communicating technical content to general audiences Good to have skills: • Experience in Legal, eDiscovery, or Information Governance • Prior work or support experience in legal or information governance functions is preferred. • Ability to manage Increasing Workload and Complexity • Capacity to supplement existing team efforts and handle growing volume and complexity of cases. • PHP Experience Responsibilities: • Collect data from products across the company for use in legal matters • Automate analyses and author pipelines via SQL and Python based ETL framework • Build dashboards to bring your pipelines to life for non-technical partners • Stay up to date on new structured data sources within the Company as they are developed and help non-technical partners understand the use and content of these sources • Create and maintain internal documentation on pipelines, tools, data sets • This is a highly collaborative and cross-functional role: • Partner with lawyers across the Legal department to understand their data needs • Partner with economic consultants to develop product and financial models • Partner with data science teams to ensure accuracy of analyses • Partner with infrastructure and data engineers to manage large data sets effectively