CenturyLink (NYSE: CTL) is a global communications, hosting, cloud and IT services company enabling millions of customers to transform their businesses and their lives through innovative technology solutions. CenturyLink offers network and data systems management, Big Data analytics and IT consulting, and operates more than 55 data centers in North America, Europe and Asia. The company provides broadband, voice, video, data and managed services over a robust 250,000-route-mile U.S. fiber network and a 300,000-route-mile international transport network.
Roles and Responsibilities (Position Expectations)
Responsible for delivering on client data science engagements with high performance computing techniques to yield critical insights from large volumes of structured and unstructured data. This position not only oversees and executes the analysis but also creates analytical tools, applications, and frameworks to continually leverage previous work and insights.
Job Responsibilities include:
-------- Selects and implements methodologies from statistics/machine learning and computational science to answer research questions
-------- Partners with business leaders across client organization to help assess business needs and define research questions
-------- Predicts outcomes based on rigorous experimental design and statistical method
-------- Synthesizes insights and documents findings through clear and concise presentations and reports
-------- Creates repeatable solutions through written project documentation, process flowcharts, layouts, diagrams, charts, code comments and clear code
Required Skills and Experience
--------- Minimum of 12+ years of experience in applied data science and programming in one or more of the following industries: Financial Services, Healthcare, Retail, ecommerce, Consumer Packaged Goods, Oil & Gas, Telecommunications or Manufacturing
--------- MS/PhD or commensurate experience in Statistics/Econometrics/Machine Learning or other quantitative discipline
--------- The ideal candidate will have a wide range of experience analyzing and deriving insights from data
--------- He/she will be good at translating complex technical concepts into actionable tactical and strategic insights and communicating them persuasively to our internal teams and managers as well as clients and partners.
--------- Strong background in Big Data and Advanced Predictive Analytics including an exposure to areas such as Artificial Intelligence, Deep Learning, Intelligent Bots, Reinforcement Learning, Neural Networks.
--------- Strong consulting experience (e.g. with a Big 4) with demonstrated success related with delivering client data science engagements.
--------- Able to demonstrate advanced computing and analytical skills with particular knowledge and understanding of the following areas:
o-- Statistical modeling (Lease Squares & Logistic Regression, GLM, Segmentation, Clustering, Dynamic Bayesian Networks, etc.)
o-- Machine Learning (Neural Networks, Random Forests, Support Vector Machines, etc.)
o-- Statistical analysis software (Python, R, Spark MLlib, PySpark, SparkR, SAP Predictive Analytics, MATLAB, SAS, SPSS,- etc.)
o-- SQL Programming experience in a relational database environment (Oracle, MS SQL Server, Teradata environment); Knowledge about in-memory architectures (SAP HANA, MemSQL, Gigaspaces).
o-- Data Science visualization tools (R Shiny, Tableau, Qlikview, SAP Lumira, etc.) as well as traditional Reporting/BI tools (Business Objects, MicroStrategy, Cognos, etc.)
o-- Relational (SQL) and non-relational databases (Hadoop, Cassandra, etc.)
--------- Ability to quickly learn and apply new tools as needed
-Our ideal candidate would have Strong Big Data skills but also understand data science overall-understand and know how statistical/machine learning models can be built natively on the Hadoop environment using Spark (python, Microsoft R Server, SparkR, SparkML).- People that have both sets of skills are critical to our success