Big Data Analytics Engineer

The Allstate Corporation is the largest publicly held personal lines property and casualty insurer in America. Allstate was founded in 1931 and became a publicly traded company in 1993. Allstate offers car insurance, home, property, condo and renters insurance, plus insurance for recreational vehicles like motorcycles, boats and more.

* This role is responsible for leading efforts of medium to high complexity and critical tracks of delivery of Big Data platforms to make decisions. This includes the development and recommendation of new Big Data systems for analyzing data; the coding & development of advanced analytics solutions to make/optimize business decisions and processes; searching for and integrating new tools to improve descriptive, predictive, and prescriptive analytics; and discovery of new technical challenges that can be solved with existing and emerging Big Data hardware and software solutions. This role will also begin project management of complex projects. The Big Data Engineer job family is accountable for end to end engineering of data solutions which includes designing and building systems for data storage and analytics that enable Allstate analysts to make better decisions to achieve Allstate’s goals.

* Make major contributions to the Big Data direction and strategy for the group in partnership with their peers. * Executes highly complex functional work tracks for the team.Drives the execution of operational/technical objectives for data analytic outputs and business solutions. * Is an active technical leader within the department * Partners with Allstate Technology teams on Big Data efforts. * Partners closely with peers in the department to ensure holistic Big Data solutions for our data science community and analytic users. * Identifies new areas of data, research and Big Data technology that can solve business problems * Utilize effective project planning techniques to break down complex projects into tasks, manage scope of projects, and ensure deadlines are kept * Leverages, contributes and uses Big Data best practices / lessons learned to develop technical solutions used for descriptive analytics, ETL, predictive modeling, and prescriptive “real time decisions” analytics * Influences within the department on the effectiveness of Big Data systems to solve their business problems. * Is recognized as an expert in Big Data and is influential within the department. * Develops technical solutions using Big Data techniques in data & analytics processes. * Supports Innovation; regularly provides new ideas to help people, process, and technology that interact with analytic ecosystem. * Develops and builds frameworks/prototypes that integrate Big Data and advanced analytics to make business decisions. * Implements new areas of Big Data technologies, (ingestion, processing, distribution) and research delivery methods that can solve business problems. * Understands the Big Data related problems and requirements to identify the optimal technical approach. * Works with QR&A peers to ensure efforts within owned tracks of work will meet their needs. * Drives multiple tracks of complex work within the research group. * Identifies and develops Big Data sources & techniques to solve business problems. * Co-mingles data sources to lead work on data and problems across departments to drive improved business & technical results through designing, building, and partnering to implement models. * Manages various Big Data analytic tool development projects with midsize to large teams. * Executes on Big Data requests to improve the accuracy, quality, completeness, speed of data, and decisions made from Big Data analysis.

* 3 - 5 Years of experience or equivalent skills & ability * Master’s or PhD preferred in a quantitative or scientific field such as computer science, computer engineering or equivocal experience. * Experience in using software development to drive data science & analytic efforts. * Experience with database & ETL technologies. * Experience with various data types (e.g. Relational, Unstructured, Hierarchical, and Linked “Graph” Data). * Experience in developing, managing, and manipulating large, complex datasets. * Experience in working with statistical software such as SAS, SPSS, MatLab, R, CART, etc. * Proven ability to code and develop prototypes in languages such as Python, Perl, Java, C, R, SQL, and XSLT. * Ability to communicate and present advanced technical topics to general audiences. * Leading project teams of various skills levels. * Understanding of predictive modeling techniques a plus.