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Westlake

    Senior Data Scientist - Westlake, United States - BANTA GLOBAL TURNKEY LLC

    BANTA GLOBAL TURNKEY LLC
    BANTA GLOBAL TURNKEY LLC Westlake, United States

    1 week ago

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    Description


    Company Description RRD is a leading global provider of marketing, packaging, print, and supply chain solutions that elevate engagement across the complete customer journey.

    The company offers the industry's most trusted portfolio of creative execution and world-wide business process consulting, with services designed to lower environmental impact.

    With 22,000 clients, including 93% of the Fortune 100, and 32,000 employees across 28 countries, RRD brings the expertise, execution, and scale designed to transform customer touchpoints into meaningful moments of impact.

    Job Description This individual will be an integral part of the team to improve efficiency and make sure our products/services are generating maximum revenue.

    The Data Scientist will define data collection requirements, perform statistical analysis on data sets and create reports.

    He/She will place a lead role in business intelligence, advanced analytics, data integration, and master data management efforts and will be involved with traditional application development projects where necessary.

    This position will support revenue-generating projects and will have a significant impact on RR Donnelley's client service business profitability.


    Responsibilities:
    Standard tasks of data mining, data collection, predictive variables, and creating algorithms.

    Evaluating existing technologies and/or creating new machine learning and data mining algorithms, designing and executing offline/online experiments Prepares comprehensively documented observations, analyses, and interpretations of results including technical reports, summaries, protocols, and quantitative analyses Works with big data and distributed computing platforms Create, implement and evaluate alternate models through various theoretical approaches.

    Research and develop statistical learning models for data analysis. Develop and deploy predictive models based on historical data that provide future predictions about customer behavior. Collaborate with business stakeholders and engineering departments to understand company needs and devise possible solutions. Communicate results and ideas to key decision makers and possess the ability to present findings to non-technical audiences. Implement new statistical or other mathematical methodologies as needed for specific models or analysis. Optimize joint development efforts through appropriate database use and project design. Understand the flow of data, business processes/technical interfaces that would be created or impacted. Identify and document sources of existing data as well as new data. Understands use of master and reference data including sources and contributors.

    Document the source-to-target mappings for both data integration as well as web services (consumer/provider mappings) that can be easily understood by the project team members with data quality and transformation rules.

    Ensure conformance to enterprise data governance policies around information risk and data protection guidelines. Identify other opportunities that will help improve operations. Guide and lead the team through various projects, keep track of their progress and provide feedback. Mentor and train junior staff and/or interns. Qualifications Bachelor's Degree in Statistics, Mathematics, Actuarial Science, Computer Science, Machine-learning, or related fields required Master's Degree preferred.

    10+ years of relevant work experience in analytics, data mining, and/or data modeling Understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques, and recommendation and optimization algorithms.

    Knowledge of SQL, R, and/or Python and machine learning techniques are required. Knowledge of SAS and/or SPSS is required. Working knowledge of *nix shells and file systems. Comfortable using Git variant version control systems.
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