Rauxa

  • Data Scientist

    Job Location US-NY-New York | US-NY-New York
    Job ID
    2018-1833
    Category
    Data & Analytics
  • Overview

    The Data Scientist will be part of a team that will help expand data driven advanced analytics at Rauxa by engineering solutions and products with data science with agility. The Data Scientist that approaches solutions with creativity grounded in key business decisions for our clients customers and our partners will further elevate Rauxa Data Intelligence.   

     

    Elevation includes solution design and execution of advanced analytical data exploration, mining, inference, models and systems utilizing multiple traditional and non-traditional media measurement data sets that empower marketers to make the right decisions and engage their customers with meaningful messaging.

    What you'll do:

    • Consult for and/or lead projects that encompass direct interaction with internal business clients and peers at external clients
    • Identify opportunities to use statistics and machine learning to create advanced analytics and value-added insights at scale
    • Have an impact on consumer scale datasets using the disciplines of data science, data engineering, and their application in marketing and advertising
    • Meet with customer’s data science teams to discuss our models and our roadmap
    • Develop and active 2nd party data assets from 1st, 3rd, private and public data sources
    • Identify new opportunities to leverage data assets
    • Propose infrastructure to accelerate the pace of model exploration and improve model serving and maintenance
    • Engage in meticulous experimentation to evaluate and compare models
    • Write internal and external facing documentation describing models and approaches
    • Deploy models to production and maintain them
    • Develop and deliver high-impact tools and insights comprised of aggregated data sets and advanced algorithms with a clean user experience
    • Drive the collection and manipulation of new data and the refinement of existing data sources
    • Translate inferences from advanced analytical methods and complex models to non-technical business audiences at all levels of the organization
    • Acquire (fast) and apply programmatic industry knowledge and leading choices of Machine Learning, Statistics, Optimization algorithms
    • Grow Natural Language Processing, Deep Learning, Reinforcement Learning, for optimization
    • Apply time series analysis expertise to relevant challenges

    Who you are:

    • Demonstrated proficiency in statistical methods (i.e., parametric and non-parametric regression, time-series, panel data analysis, survival analysis, etc.) and machine learning techniques (i.e., methods of supervised and unsupervised learning such as clustering, regression, classification, ensemble methods, etc.)
    • Deep understanding of statistical/probabilistic analysis and linear algebra
    • Team-oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools
    • Strong communication skills including ability to develop presentations and present insights and recommendations
    • Ability to convey complicated problems, solutions, processes and systems to all levels of the organization
    • Ability to work in a flexible, dynamic and fast-paced team and client service environment;
    • Able to move fast and manage multiple priorities across a mix of ad-hoc and operational projects 

    Education/Experience Required:

    • Majored in Statistics, Engineering, Math, Economics, Computer Science or other technical fields (PhD preferred)
    • 7+ years of experience working in a fast-paced, high-tech or marketing agency environment
    • Proven experience with statistical modelling and/or machine learning
    • Demonstrated experience with data visualization techniques
    • Experience with tools and technologies enabling self-sufficiency in data analysis and modeling: R, Python, SQL, or other scripting languages
    • Expertise in cluster compute environments like Kafka, Spark, Hive and/or Hadoop or their AWS and Google equivalents
    • Experience publishing and or presenting work at a leading industry conference, journal or publication (like kaggle) is a plus

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