As Director, Data Science & Machine Learning you will be the leader of a growing team responsible for envisioning and implementing the Analytics & ML practice for the global UPS enterprise. This highly visible team will work with executive stakeholders in Operational, Customer and Enterprise Business Units and Solution Delivery Groups to understand challenges, assess data needs and develop strategies, roadmaps and solutions to address complex Logistics challenges. The team will advance and evangelize the adoption of Advanced Analytics and Machine Learning techniques and algorithms driving a pervasive Data Drive culture at UPS. The ideal candidate will combine demonstrated experience working with Business and Technology stakeholders to drive out business and customer value using Data and Analytics solutions, expert Data Science, AI/ML/Open Source/Tech/Big Data management knowledge, and demonstrated success establishing an enterprise scale Data and Analytics Practice and Model.
Evolve the Enterprise roadmap and strategy to leverage Analytics/ML techniques and models to rapidly drive business and customer value based on assessing business plans for the greatest areas of opportunity.
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.
Collaborate with internal, external and cross functional teams to lead enterprise efforts to bring in new data science technologies, frameworks and methodologies.
Work with Learning and Development teams to create training programs to grow and enhance technical and business team skills and knowledge.
Evangelize the benefits of incorporating Analytics/ML with the goal of identifying new opportunities for embedding algorithms into existing business processes.
Lead a team of Data Scientists to conduct Proof of Concept (POC) projects as needed to vet techniques and potential business value models.
Lead a team of Data Architects and Analysts 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.
Consult with Infrastructure teams on development of automated processes to cleanse and integrate datasets from disparate sources.
Work with Infrastructure teams to evaluate and implement new analytics platforms, services and methodologiesAdditional, related duties as required
Job Qualifications:
Master’s Degree or higher in Statistics, Mathematics, Data Science, Computer Science or related disciplines.
5+ years of experience in progressive roles involving business analysis/business intelligence.
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 in direct management of each of the following (teams, projects, customer relationships).
Minimum of 5 years of experience implementing solutions with one or more key technology platforms including:
Hadoop/HDFS (HBase, Cloudera, Hortonworks, MapR)
NoSQL databases (Couchbase, Cassandra, MongoDB, HIVE, etc.)
Cloud-based/hosted Analytics Platforms
MDM platforms
Azure (HDInsight, Data Lake Analytics and Data Lake Store)
Spotfire, Tableau, Qlikview, or related technologies
Experience with SAS/R, and/or Python.
Demonstrated passion in building solutions to answer business questions and improve business processes.
Formal training in descriptive statistics, inferential statistics and statistical methods such as regression.
Formal training in machine learning and advanced analytical methods such as classification, clustering, association analysis, optimization, etc.
Skill in enterprise-level visualization and analytics platforms.
Experience simplifying and presenting complex analytical concepts to management including C-level executives
Excellent verbal and written communication skills
Strong team building skills.
Additional Preferred Skill Requirements:
Experience with database technologies, Master Data Management, Big Data, Data Warehousing, Business Intelligence, Data Visualization, and Analytics Platforms.
Experience working with diverse teams.Experience with software scalability.
Proven experience in data warehouse, analytics platforms, and/or big data architecture design.
Strong analytical, communication and interpersonal skills.
Strong contract negotiation and proposal writing skills.
Good communication (written and oral).
Good organizational, multi-tasking, and time-management skills.
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