• Marketing Data Scientist

    Job Locations US-CA-Irvine
    ID
    2018-2134
    Shifts Available
    Friday, Monday, Thursday, Tuesday, Wednesday
    Category
    Marketing
  • Overview

    We are Drybar, a blow dry bar, and we set out to shake up the beauty industry in our own, specialty way. We believe in doing one thing and being the best at it. For us, that’s blowouts. In fact, our tagline says it best: No cuts. No color. Just blowouts. What started with one shop in Brentwood, CA has grown to over 100 locations across 25 markets, with more to come.

     

    Drybar is seeking a data scientist to join our Marketing team. If you have a passion for “wowing” business leaders with progressive analytics techniques, leading projects focused on optimizing marketing effectiveness and driving marketing innovation and working with managers who “get” the work you are doing and support the value of analytics to drive brand results, then Drybar is the place for you!

     

    What we're all about:

     

     

     

    Responsibilities

    • Data Munging 
      • Collect data from a wide variety of corporate databases and Excel files.
      • Utilize your toolset in regular expressions to extract information from un-structured text documents and the web.
      • Handle missing data through an algorithmic approach such as multiple imputations to enable insights in sparse and messy data. 
      • Use your inner whiz-kid to feature engineer the data to boost model accuracy.
    • Predictive Modeling
      • Utilizing your algorithmic/programming toolkit, build predictive models to drive acquisition, engagement and retention and improve growth and profitability, and other such key performance indicators for our business.
      • More specifically, apply algorithms equal or similar to the following: elastic net regularization for regression, random forests, generalized boosted models, generalized additive models, support vector machines, neural networks, and time-series forecasting. Ability to communicate implications of the level of confidence in each of the models.
      • Implement formal modeling processes from end to end including data gathering, data profiling, numerical model building, calibration, cross-validation, putting product into production, etc. 
      • After building the models, pilot “scorecards” to track model performance and calculated improvement to business. 
      • Explain complex modeling approaches in layman’s terms and discuss modeling results and business case impacts with non-technical business users.
    • Test/Learn Analytics
      • Develop a portfolio of test and learn programs, lead the test design and measurements/goals and manage the day-to-day execution of the corresponding analyses. 
      • Establish robust A/B and fractional factorial testing methodologies including sample size requirements for readability and go/no-go criteria for scaling.
      • Lean-out testing processes to cut end-to-end cycles times and accelerate weekly test cadence.
      • Manage testing calendar and minimize test collisions given test objectives and audiences.
      • Establish tracking of value identified, validated in-market, and scaled across marketing channels and eCommerce.
      • Create, maintain, and deliver dashboards and reports for KPI results from test measurements and communicate results to key stakeholders.
      • Monitor and interpret results and suggest next steps for new test and rollout of programs to key stakeholders. 
      • Conduct ad hoc analysis for internal partners as requested, including in-depth funnel and conversion analysis 
      • Support the maintenance and development of web analytics platforms.
    • Customer Glidepath and Audience Management
      • Develop and maintain comprehensive customer segmentation models and recommendations for key focus segments.
      • Identify targeted audiences to optimize marketing communications for digital media, on-site personalization, and one-to-one marketing (e.g., email, SMS, and direct mail) leveraging transactional data, online-browse behaviors, and 3rd parties.
      • Develop thought leadership on best variables and fields to define key audiences for customer glidepath management efforts.
      • Partner with IT to build, manage, and refresh audiences in relational databases and campaign management platforms to execute segmented marketing programs.
      • Lead deep dives to identify highest performing audiences in digital media, on-site personalization, retargeting, and one-to-one marketing campaigns.
      • Develop audience targeting plans for media buying, on-site personalization, and one to one vehicles.
      • Collaborate with vendors to build audiences in external databases and systems (e.g., DMP, third-party demographic data, etc.).
      • Execute ad-hoc analyses as requested by leadership for development of segmented contact strategies.
      • Create and maintain reports detailing performance of key audiences and communicate results to key stakeholders.
    • Mixed Media Modeling Emphasis
      • Develop and maintain multi-touch attribution models across digital and non-digital marketing channels.
      • Estimate causal impact of marketing activities on financial outcomes in the short and long term. 
      • Integrate Marketing ROI models with multi-touch attribution models (e.g., consistent media taxonomy, rationalize ROI estimates).
      • Prepare quarterly media optimization scenarios to inform media plans, financial forecasting, and target areas for efficiency gains.
      • Provide insights to marketing and channel leads on cost to acquire, value of digital engagement, and cross-channel impact of media.
      • Ensure high quality inputs into media mix models including accurate media spend by market, pricing/promotion position, competitor spend, and channel support.
      • Establish and maintain expert knowledge of the latest methodological innovations in marketing mix modeling.

    Qualifications

    • Bachelor’s degree in mathematics, business, statistics, economics, computer science or equivalent combination of education and experience. 
    • 2-5 years of directly related experience and strong proficiency of predictive modeling techniques, test/learn, customer segmentation and mixed media modeling.
    • Successful track record of applying complex analytics techniques in a retail company, ecommerce or consumer brand.
    • Strongly motivated to be a player in a team which is constantly working to improve themselves through discovering new analytics techniques and software tools to improve the quality of our work.
    • Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses.
    • Knowledge of digital marketing principles such as funnel optimization, UX, SEO & Landing Page optimization & experience in running A/B tests for campaigns and deriving customer insights. 
    • Proficiency in Microsoft Office Suite, SQL, and at least one of the following: SAS, R, and/or Python.
    • Strong verbal and written communication skills; ability to present complex information in an easy-to-understand manner with clear recommendations based on data insight.
    • Adaptability and the capability of multi-tasking and strong time management.
    • Thrive in a fast‐paced, entrepreneurial environment.

     

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