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Director, Data Science (Insights & Analytics)
US Foods Holding
Chicago, IL, United States
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Description
The Director Data Science (Insights & Analytics) leads the integration of mathematics/statistics, computer programming, ETL and data transformation, software development, and high-performance computing. Responsible for maintaining the integrity of analytical assets, including derived or transformed data, models/algorithms, and related technical code (e.g., machine learning tools, recommendation engines, automated scoring systems, etc.). Responsible for regulating usage of data or code for business application, including the development, testing, and productionalization/scaling of models and statistically-based tools. Leads a team of Data Scientists responsible for data mining, integration, and preparation for use in advanced analytics. Responsible for prioritization and Data Scientist resource allocation across the enterprise. Responsible for the monitoring of model integrity and performance and works closely with Decision Sciences to continuously improve/enhance advanced analytics effectiveness. Serves as the business owner for all advanced analytics tools, including their access and application. Works closely with Food Genius team to ingest, catalog, and disseminate third-party intelligence for analytics use. Is a principal participant within the Data Governance committee.
Essential Duties and Responsibilities
Data Science Practice Management:
• Establish an enterprise-wide practice model that grows and matures the Analytics/ML talent pool, accelerates the use and delivery of Analytics/ML in solutions and broadens organizational utilization for maximum impact
• Develop and identify curriculum sources to ensure Data Science practice is on track with rapid development and evolution of industry-wide Data Science practices, including processes, methodologies, and technologies
• Collaborate with internal, external and cross functional teams to lead enterprise efforts to bring in new data science technologies, frameworks and methodologies
• Lead a team of Data Scientists to develop and implement data strategies and governance model to mine and manage large scale data sets to support Analytics/ML models and algorithms
• Seek and refine data enrichment methods and new internal and external data sources
• Work with Infrastructure teams to evaluate and implement new analytics platforms, services and methodologies
Data Management:
• Serve on the Data Governance committee to help identify data integrity issues, process enhancements, and new governance routines
• Develop and oversee protocols for cloud-based data management (in partnership with Data Engineering team) and data integration across platforms to facilitate business intelligence and advanced analytics programs
• Drive efficiency in database designs within the cloud architecture and accountable for driving cost efficiency as data requirements continue to scale
Data Preparation and Transformation:
• Develop and oversee data preparation and ETL processes with a specific emphasis on driving scalable, repeatable processes with existing tools (creating efficiency through collaboration)
• Partnering with Food Genius and Decision Sciences, oversee process, methodology, and quality control for data transformation needs as required for model development
• Work with Data Governance to establish process and protocols for the acquisition and stewardship of newly derived or acquired data elements, including third-party data
Advanced Analytics Scalability:
• Collaborate closely with Decision Sciences on model design and testing (research and development process) to create pragmatic, scalable, and results-driven proofs of concepts for piloting
Model Management, Collaboration, and Enhancement:
• Develop and oversee protocols for model productionalization using existing tools
• Establish and maintain collaboration platform for the efficient use of code and algorithms across models. Create an ecosystem of common code to limit redundancy and drive consistency in quality across model designs
• Establish and oversee testing protocols for model integrity to identify when changes or enhancements need to be employed dynamically to sustain business performance
Policy on Third Party Unsolicited Resume Submissions
Any employment agency, person or entity that submits a résumé into this career site or to a hiring manager does so with the understanding that the applicant's résumé will become the property of US Foods. US Foods will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
Employment agencies that have fee agreements with US Foods and have been engaged on a search shall submit résumé to the designated US Foods recruiter or, upon US Foods authorization, submit résumé into this career site to be eligible for placement fees.
Qualifications
Education / Training:
• Master’s Degree or higher in Statistics, Mathematics, Data Science, Computer Science or related disciplines
Related Experience:
• 8+ years progressive analytics leadership experience required including supervisory positions within Retail, CPG, Foodservice, and Distribution/Transportation or like vertical with a high volume of transactional and operational data
• 5+ years of experience in Analytic Software Development Lifecycle
• 5+ years of experience as a proven leader generating Advanced Analytics solutions to address business needs
• 5+ years of experience leading teams
• Strong programming ability
• Well versed in Agile software development practices
• Fluency with Python
• Comfortable in quickly changing AWS ecosystem
• Experience developing models, monitoring them in production, and measuring their business impact
• Experience implementing solutions with one or more key technology platforms including:
◦ Spark
◦ Hadoop/HDFS (HBase, Cloudera, Hortonworks, MapR)
◦ NoSQL databases (Couchbase, Cassandra, MongoDB, HIVE, etc.)
◦ Cloud-based/hosted Analytics Platforms
◦ Tableau or related technologies
◦ Data preparation, processing, and model management/collaboration tools
◦ Metadata management applications
◦ Machine-generated data visualization platforms
• Exposure/familiarity with NLP
• Experience with software scalability
Knowledge / Skills / Abilities:
• Business Strategy and Analytics
◦ Excellent business acumen
◦ Excellent data manipulation and analysis skills
◦ Ability to think logically and analytically
◦ Detail oriented
◦ Able to take complex, ambiguous problems, break them down into smaller parts and problem solve to come up with a whole, integrated and strategic solution
◦ Creative problem solver
◦ Competency/fluency with various statistical methodologies/applications, including classification, survival analysis, regression, design of experiments, time series, optimization, and machine learning
• Self-direction and Team Work
◦ High degree of motivation
◦ Ability to work independently and within a team
◦ Ability to build consensus and lead work streams
◦ Highly organized with the ability to multitask and prioritize workloads
• Communication
◦ Excellent verbal and written communication skills
◦ Strong presentation skills
◦ Ability to communicate complex concepts clearly
◦ Ability to influence change within complex organizations
◦ Ability to relate to others
◦ Advanced knowledge of information visualization best practices and strategies
• Proficiency in the following required:
◦ MS Office Suite, including:
# Microsoft Outlook
# Microsoft Excel (e.g., pivot tables; slicer; vlookup, hlookup; formulas; if then statements)
# Microsoft PowerPoint (e.g., update presentations; create graphs, tables and other data visualization techniques)
# Microsoft Word
◦ Agile methodology
◦ Source control (e.g., GitHub)
◦ Data querying methodologies and languages (e.g., SQL)
◦ Coding using open source technology (e.g., Python, R)
◦ Cloud-based data warehouse environments (e.g., Amazon Web Services, Snowflake/Redshift)
◦ Other data mining and preparations tools (e.g., Alteryx, Talend)