DSW Designer Shoe Warehouse

About DSW Designer Shoe Warehouse

 

Job Category:

Database

Country:

United States

Postal Code:

43219

Approximate Salary:

Not Specified

Data Scientist Job

DSW Designer Shoe Warehouse - Columbus, Ohio

Posted: 12/15/2018

Req #: 84617 
Location Name: Home Office, Columbus 
Department: Marketing 

 

At DSW, we believe in the power of shoes. We understand shoes bring out something great from within, and since 1991 we've been helping everyone feel the rush of finding that perfect pair. So when you work for DSW, you become a part of all that. A family whose core values are comprised of passion, accountability, collaboration, and humility. You become one of us, You become a Shoe Lover!

 

General Summary:  The Data Scientist will develop detailed deep-dive analytics, statistical models, and other machine learning analytics. This individual will be responsible for customer analytics and modeling to drive increased personalization for DSW’s loyal customers. The role will synthesize business data into powerful models and insights to drive decisions which propel the business forward.

Reports to: Advanced Data Analytics Lead

Essential Duties and Responsibilities:

  • Captures business opportunities by developing machine learning models and other statistics-based analytics
  • Develops software programs, algorithms, and other mathematical approaches to 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 with business partners to take business problems or knowledge gaps and identifies analytical opportunities to drive innovative decision making
  • Extracts key insights from analytical projects into a format easily understood by business partners, both technical and non-technical; presents insights and recommendations to business leaders
  • Accesses, combines, aggregates, and cleans data sets from multiple key sources (RDBMS, Big Data Storage, Web…) 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 the data presented to the business
  • 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 in all levels of analytical projects

     

Required Skills and Competencies:

  • Excellent verbal communication skills for all audiences, both technical and non-technical
  • Ability to create visualizations, summarize, and present complex analytical techniques, data, and recommendations
  • 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 area

 

Qualifications

 

Experience:

  • Experience with R or Python for statistical modeling and other machine learning applications
  • Experience with SQL and NoSQL database environments and is comfortable aggregating and combining large, complex data sets
  • Proven track record of various machine learning techniques to create models that drive significant business results
  • 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…)
  • Bachelor’s Degree with 4 years of experience required,
  • Master’s Degree with 2 years of experience, or PhD 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…)
  • Experience with Google Cloud Platform (BigQuery, Compute Engine, DataLab, ML Engine…)
  • Knowledge of any current public cloud offering (Azure, Google, AWS…)
  • Experience with dashboard design and data visualization tools (MicroStrategy, Tableau, R Shiny…)
  • Experience or familiarity with at least one scripting language (Python, Java…)

DSW believes that all persons are entitled to equal employment opportunities. We do not discriminate against any protected class including race, color, religion, religious creed, gender, sex, national origin, age, physical disability, mental disability, medical condition (defined as genetic information or impairments related to cancer), ancestry, marital status, family care leave, military and veteran status, citizenship status, sexual orientation, gender identity, gender expression, genetic information, or based on any protected category under federal, state, or local laws. DSW also makes reasonable accommodations for qualified applicants and associates with disabilities unless doing so creates an undue hardship, in accordance with all legal requirements. Any applicant requiring a reasonable accommodation during the application process or applicant who requires an accommodation to perform the essential functions of the job should request for accommodations by asking to speak with a Store Manager, District Manager, and Regional Manager, or by contacting Human Resources at HR-DSW@dswinc.com. DSW will work with the individual to attempt to identify a reasonable accommodation that will not impose an undue hardship on DSW.


 

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