United States of America
Job Summary: The Director of Advanced Analytics Platform and Data Services is responsible for the strategic vision and implementation strategy to support Wawa’s Business Intelligence, Big Data and Advance Analytics needs. Working with the business data science and analytic teams, this role will establish and operationalize Wawa’s enterprise data and analytical technology capabilities to achieve a fully integrated digital information and intelligence eco-system. The Director will set the technical direction of platforms, drive innovation, and provide operational leadership of the enterprise analytics, intelligence and data science platforms and services.
Lead data related activities (data discovery and organization on SQL/Big data stack, cleansing and data prep) to support development of new data science approaches and methodologies (e.g. neural nets, CART (Classification and Regression Trees), Bayesian methods, etc.) to improve operations and business outcomes.
Deliver innovative solutions (machine learning, artificial intelligence, advanced visualization, real-world complex data strategies, retail informatics) that align with business needs (today and tomorrow) to create Data-as-a-Service, Analytics-as-a-Service and predictive intelligence platforms for the Company.
Establish services and platforms to accelerate the adoption and value realization of emerging technologies including but not limited data science, natural language processing, content analytics, augmented reality, machine learning / artificial intelligence.
In partnership with the business analytics teams, establish platform strategies and evolution of enterprise data and analytical capabilities including shared services (i.e. central governance, data stewardship, operational leadership-resourcing-prioritization)
Work cross-functionally to understand relevant product direction. Articulate an enterprise integrated data roadmap to model future state capabilities and be critically focused on developing new functional assets to accelerate the data services product development.
Work cross-functionally to develop effective communication and training vehicles for other IT and business teams on platform services and roadmaps, and elevate line function skills-sets in adeptly executing advanced analytics using central ways of working and tools.
Provide subject matter expertise in several of following analytic areas: machine learning, artificial intelligence, deep learning, recommendation engines, predictive modeling, web/app analytics, A/B testing, search algorithms, data visualization, natural language processing, and content analytics.
Be a thought leader in Big Data, Data Analytics & Data platforms and constantly innovate the products to remain ahead of the curve. Working with the business champions and stakeholders help build a data-driven, decision-making culture. Drive self-service models in analytics and data preparation.
Enable Wawa’s analytics capabilities including the exploitation of big data and sourced data as well as the exploration of dark data, using a combination of open source, cloud and social era tools and techniques for data analytics, mining and visualization.
Contribute to and support Master Data Management (MDM) efforts that enable how data will be used for business reporting and analytics and how external data will supplement Wawa generated information.
Enable new data assets, types and sources of data to be made available to drive business innovation throughout the organization e.g. IoT. Define processes for the effective, integrated introduction of new data.
Partner with Risk and Security teams to create policies and controls for the appropriate protection of enterprise information assets through a defined life cycle, from acquisition or creation to end of life.
For projects, ensure realistic estimates, budgets and deadlines are established and a support project structure and reporting is established for successful execution.
Responsible for developing and managing department budget and contributing to the overall IT budget development.
Provide overall direction and support for team and monitor and assess individual work in accordance with high standards of excellence. Provide feedback, coaching, support, opportunities for development, complete performance appraisals, take corrective action when appropriate, and participate in hiring decisions.
Effective conceptualization, pattern recognition and design-thinking skills.
Capable of translating analysis results into business recommendations
Communicate effectively both orally and in writing
Analyze information, understand implications, and effectively propose solutions
Highly developed consultative, facilitative and project management skills
High degree of professionalism and confidentiality
Ability to effectively negotiate with internal and external constituents
Handle multiple priorities simultaneously
Work collaboratively with cross-functional teams
Establish and maintain a working environment conducive to positive morale, individual style, quality, creativity, and teamwork
Ability to build strong trusting relationships with business partners
BA/BS degree in Computer Science, Mathematics, related technical field or equivalent practical experience
8 -10 years of experience with data platforms and services
10+ years of experience working data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments
8 - 10 years of experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments
5-10 years of experience in enabling complex data science efforts
Experience working with big data, information retrieval, data mining or machine learning as well as experience in building multi-tier high availability applications with modern web technologies (such as NoSQL, MongoDB, SparkML, Tensorflow)
Experience in quantitative analytics (marketing analytics, statistical modeling, machine learning, digital attribution, forecasting, optimization, predictive analytics, Realtime Analytics)
Knowledge of design, data structures and algorithms. Demonstrated knowledge of private and public cloud design considerations and limitations in the areas of virtualization, global infrastructure, distributed systems, load balancing, networking, massive data storage, Hadoop, MapReduce, and security
Exposure and understanding of existing, new and emerging information technologies, and high scale data processing environments
Experience programming in Python and R
Strong knowledge of IT disciplines and trends
Strong knowledge of Business Process management discipline and methodology
Strong knowledge of Business Intelligence/ Enterprise Information Management
Basic financial management knowledge
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