Senior Data Science Manager: Supply Chain Forecasting

The pay range provided is not indicative of Sysco’s actual pay range but is merely algorithmic and provided for generalized comparison. Factors that may be used to determine rate of pay include specific skills, work location, work experience and other individualized factors

POSITION SUMMARY:

Sysco is seeking a Senior Manager, Data Science to help drive the development of industry-leading predictive models as part of its Enterprise Analytics Team. As a Sr. Manager, you will own the technical development of a portfolio of domain-specific predictive models in support of a functional group (Pricing, Merchandising, Supply Chain & Logistics, etc).

There are two primary responsibilities of the Sr. Data Science:

• Develop predictive analytics (hands-on-keyboard) via statistical, machine learning, and mathematical models on Sysco’s corporate data to get actionable business insights as the technical expert in the portfolio
• Lead and coach data scientists to succeed in their areas of responsibility and in support of the domain-specific portfolio of models that you are accountable for

RESPONSIBILITIES:

• Lead the technical development of an industry-leading predictive analytics portfolio in support of key functional & business priorities (e.g., demand generation, assortment optimization, supply chain design & optimization)
• Work with Sr. Directors and Directors throughout Sysco to frame business opportunities and develop appropriate analytic strategies. Ensure the appropriate analytical techniques are used to solve those business opportunities.
• Implement data science models and visualizations using Python, Tableau and open source libraries
• Manage, attract, coach, retain, and motivate a world class team of scientists and engineers
• Lead multiple projects simultaneously and help team resource planning.
• Perform regular code reviews and give feedback on approach and coding standards to junior data scientists.
• Design and execute experiments to validate solutions during product rollout and present results to leadership.
• Collaborate with cross-functional teams to drive business results through various use cases of customer-level in
• Work with Sysco’s technology teams on data integration to architect, build and continuously improve data assets, which are the foundation of data-driven and customer-centric initiatives
• Research industry leading analytics practices and recommend continuous improvement opportunities for Sysco
• Represent Sysco in industry events

QUALIFICATIONS:

Education and / or

Experience:

• Master’s degree + 4 years or PhD + 2 years of industry experience in management consulting, strategy, analytics, at a specialized analytics company or in an analytics organization in a corporate setting.
• Degree should be in mathematics, statistics or computer science or related field; preferred from a top tier University.
• 4+ years of experience accessing and manipulating data in SQL or No
  
  SQL database environments
• 3+ years of experience with scientific scripting languages (e.g., Python) and/or object-oriented programming (e.g., C++, Java)
• 4+ years of experience with Bayesian statistics, regression analysis (beyond linear regression), supervised learning, unsupervised learning or time series analysis required

Basic Qualifications:

• Must be able to think conceptually, strategically, and creatively with little oversight or direction (i.e. display thought leadership vs. simply do or execute something that was developed or directed by someone else)
• Must have experience initiating, driving and delivering complex analytical projects
• Able to perform quantitative analysis using appropriate analytical and visualization tools such as Python, Tableau and open source libraries
• Strong software design and OOP fundamentals (must be functional in nearly any language)
• Demonstrated experience using machine learning algorithms in a commercial setting
• High proficiency in the use of statistical packages, understanding advantages and limitations of each
• Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
• Must be very comfortable with numbers and have a solid understanding of various…