Data Scientist, Margin Strategy

The primary purpose of this position is to maximize sales and margin by defining category specific promotional strategies that align to consumer/shopper segments and position us to succeed in the competitive landscape. These strategies will drive sales and margin growth, build customer baskets, and focus on traffic driving metrics. The role utilizes advanced data analytics to enable informed business decisions and initiatives.

• Establish a strategic promotional framework with Category Management to create promotional offer strategies and initiatives by category. Act as a strategic thought partner with Category Management, Finance, E-commerce, and Marketing to share and execute on data insights for promotional offers and initiatives.
• Collaborate with Category Management teams to understand internal customer shopping patterns, opportunities, and the implications for the different areas of the business.
• Support CRM Promotional strategies and integrate customer data, channels of business, and promotional results in new ways to deepen customer relationships and drive profitable retail business growth
• Leverage exploratory data analytics skills to identify promotional optimization opportunities, vendor funding variances, assortment affinities, channel productivity, all-in margin, and inventory improvements.
• Develop and utilize pertinent methods, models, algorithms needed to answer business questions. Identify key insights from analyses, cutting through large amounts of data to quickly identify trends and implications on sourcing strategy & approach.
• Identify promotional optimization opportunities and gaps by understanding the business and through application of quantitative and qualitative industry, consumer, sales, and syndicated data.
• Translate insights into action, leverage clear storytelling and data visualization to effectively share business insights and proposals to category management and senior management. Use analytics to inform promotional management decisions and support promotional funding negotiations

EDUCATION REQUIREMENTS

Education Level

Area of Specialization (Marketing, Finance, Pharmacy, Engineering/IT, etc)

Required Or Preferred

Bachelor Degree

Mathematics, Statistics, Economics or related field **

Required**

Masters Degree

Mathematics, Statistics, Economics or related field **

Preferred**

KNOWLEDGE, SKILLS AND ABILITIES

Knowledge, Skills And Abilities

Required or Preferred

Strong understanding of statistics and statistical modeling

Superior analytical and quantitative skills

Experience with managing and aggregating large amounts of data

Strong communication skills - speaking, writing, and presenting

Proficiency in analytics tools and coding (Excel, Google Analytics, SQL, Tableau/ Power BI, Alteryx, Matlab, Minitab)

Ability to use and apply machine learning, AI, and statistical analysis techniques to complex structured or unstructured data sets to answer difficult business questions

Strong financial knowledge & business acumen **

Strong Problem-solving Skills:**

Ability to take ambiguous problem and structure analytics to solve that problem

Ability to overcome roadblocks proactively and independently in working complex data sets

Passion for using data to solve complex problems

Strong interpersonal skills & ability to collaborate across teams **

Experience**

WORK EXPERIENCE

Required Or Preferred

Areas of Experience (Pharmacy, Compliance, E-commerce, Retail, etc)

7 years of experience in Retail, operations, and/or business management/consulting with a proven history of delivering results **

Required**

7 years of experience in merchandising analytics and/ or category management in retail **

Required**

5 years of experience in Merchandising, category management, or merchandise strategy **

Preferred**

5 years of experience in pricing and promotion, inventory management, and product development **

Preferred**

3 years of experience in analytics tools and coding (Excel, Google Analytics, SQL, Tableau/ Power BI

Require

The typical starting pay range for this position is between [97,600 - $150,250], although wages can vary based on experience and geography.”