POSITION: DATA SCIENTIST
The Data Scientist interprets, monitors, and analyzes data, yielding actionable information to guide decisions in wide-ranging areas. Provides related consultative services. Researches, develop, and optimizes predictive models using data science, machine learning, and statistical inference techniques for advanced analytics across procure to pay such as spend analytics, savings prediction, and business expense analysis. Sources and acquires data both internally and externally needed to build predictive algorithms. This level performs under minimal supervision includes both routine and challenging assignments.
- Data Analysts toolkit certification
- Global portal management using tools such as Balsamiq, Api using Google Postman and UML, Salesforce.com, Siebel and Google analytics
- End-end product lifecycle management using tools such as MS Project and Microsoft Office Suite
- Agile / Scrum certification
- IT product requirement Analysis using tools such as JIRA, Confluence Wiki, Microsoft Sharepoint and Survey Monkey.
- Data Visualization using tools such as Microsoft Excel, R-.
- Answer questions by developing the research methodology, gathering data and/or using appropriate statistical techniques on available data.
- Drive collection of new data and the refinement of existing data sources; apply and use algorithms or other advanced techniques to accomplish this.
- Fully analyze the problem, question existing processes and assumptions, gather data and information, find and evaluate alternative solutions, and propose the best course of action.
- Explore data from multiple angles, determine the meaning behind the data, and recommend ways to apply the data.
- Communicate, convey, and visualize informed conclusions and recommendations across an organization’s leadership structure in a manner to “tell the story” behind the data and influence how an organization approaches the challenge.
- May interact with and influence senior leaders, faculty, and/or senate with written summaries and/or presentations on assigned research.
- May delineate the information to be gathered, collect data at the project inception, prescribe how to structure the data, and specify the data warehousing structure for future access.
- Through data, may predict what actions will be taken in a designated time frame for a prescribed issue/challenge.
- May need to collaborate with other organizations to gather data. Proactively seek and locate data, including outside benchmarks or comparative data, to support or refute proposed decisions.
* - Other duties may also be assigned
- Master degree and three years’ experience in data science, machine learning, statistics, computer science, or other related fields, or a combination of education and relevant technical field experience solving analytical problems using quantitative approaches.
- Expertise in developing innovative and scalable advanced analytic techniques, tools, and platform to visualize, monitor, and optimize the performance of impactful metrics.
- Ability to build and optimize predictive analytic models leveraging data science -- machine learning, data mining, statistical inference, etc.
- Experience in leading the research and development of machine learning and predictive models such as classification, multivariate regression, clustering, anomaly detection, support vector machine, and neural network.