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Marketing Data Scientist

DATE: 
CITY:  Columbus
BRAND:  DSW
REQ #:  97471
LOCATION NAME:  Home Office, Columbus
DEPARTMENT:  Marketing

General Summary:  The Data Scientist will lead the development of detailed deep-dive analytical projects, statistical models, and other machine learning analytics that directly drive both top and bottom line for DSW. This individual will also be responsible for customer analytics and modeling to accelerate personalization for DSW’s loyalty customers. The role will synthesize business data into powerful models and insights to drive decisions which propel the business forward. This is a senior role within the marketing department and the individual stepping into the role is expected to independently lead projects without supervision, identify data sources and their location, develop insights, and influence senior leaders on business critical decisions.

Reports to: Advanced Data Analytics Lead

Essential Duties and Responsibilities:

  • Proactively identifies business opportunities and leads the development of machine learning models and other statistics-based analytics
  • Develops software programs, algorithms, and other mathematical approaches to capture new opportunities and solve business problems
  • Uses text data (reviews, surveys, IoT) to build customer sentiment machine learning models that enhance the customer experience at all touch-points
  • Develops personalized affinity models on product, brand, category, channel, etc. to drive recommended content and channel communications to the customer
  • Develops deep-dive analytics to uncover key insights of customers; unlocks competitive advantages for the business
  • Collaborates directly with key business partners and leaders to solve business problems or knowledge gaps and identify analytical opportunities to drive innovative decision making
  • Extracts key insights from analytical projects into a format easily understood by business partners and leaders, both technical and non-technical; presents insights and recommendations to senior leadership
  • Accesses, combines, aggregates, and cleans data sets from multiple key sources (RDBMS, Big Data Storage, Web, etc.) using a variety of programming languages, for use in analytical projects
  • Researches current and emerging techniques in analytics (machine learning, deep learning, AI) and applies them to solve day to day business challenges (daily demand forecast, pattern of redemption, propensity modeling, etc.)
  • Understands the broader Marketing and Retail landscapes to proactively identify analytical opportunities to impact the business
  • Applies the Scientific Method (design of experiments) to all analytical projects
  • Participates in peer review process to ensure accuracy and data integrity are present at levels of analytical projects
     

Required Skills and Competencies:

  • Excellent verbal communication skills for all audiences, both technical and non-technical
  • Ability to create visualizations, summaries, and present complex analytical techniques, data, and recommendations in simple business speak
  • Ability to effectively prioritize and manage multiple projects simultaneously
  • Ability to determine problem statements, requirements, and project plans from non-technical business partners
  • Detail-oriented with strong organizational and project management skills
  • Comfortable working with cross-functional teams of varying level (peers & superiors) and subject areas

 

Experience:

  • Experience developing machine learning and statistical models from end to end as a full stack developer
  • Experience with R or Python for statistical modeling and other machine learning applications
  • Experience with SQL and NoSQL database environments and is adept at aggregating and combining large, complex data sets
  • Proven track record of various machine learning techniques to create models that drive significant business results, with deep expertise in at least three leading methods
  • Experience with relevant analytical metrics to evaluate modeling projects using historical test sets and live in-market tests
  • Experience using command line to interact with operating systems

 

Education:

  • Degree in Analytics or other STEM field (Data Analytics, Data Science, Computer Science, Data Engineering, Applied Mathematics…)
  • Master’s Degree with 4 years of experience
  • PhD with 2 years of experience preferred
     

Preferred Qualifications:

  • High degree of intellectual curiosity and desire to learn new techniques
  • Experience with advanced state of the art techniques like deep learning, text mining, and image recognition (TensorFlow, Keras, SciKitLearn, etc.)
  • Experience with Google Cloud Platform (BigQuery, Compute Engine, DataLab, ML Engine, etc)
  • Knowledge of any current public cloud offering (Azure, Google, AWS, etc.)
  • Experience with dashboard design and data visualization tools (MicroStrategy, Tableau, R Shiny, etc.)
  • Experience with at least one scripting language (Python, R, Java, etc.)

ALREADY AN ASSOCIATE?

You must apply through our internal portal: 
click here

Why Choose A Career with Designer Brands?

Empowering associates and building strong teams poised to disrupt the retail and footwear landscape through positive change is at the core of who we are at Designer Brands.

  • Invested in helping our associates learn, develop, achieve and grow into strong leaders
  • Shared commitment to creating a culture fueled by engagement, excitement, optimism and fun
  • Dedicated to giving back and community involvement 

About Designer Brands:

Designer Brands Inc. is one of North America’s largest designers, producers and retailers of footwear and accessories. 

  • Designer Brands Inc. operates a portfolio of retail concepts in nearly 1,000 locations under the DSW Designer Shoe Warehouse, The Shoe Company, and Shoe Warehouse brands and operates leased locations in the U.S through its Affiliated Business Group. 
  • Designer Brands designs and produces footwear and accessories through Camuto Group, a leading manufacturer selling in more than 5,400 doors worldwide. 

 

 

 

 

 

 

 

 

 

 

 


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