The Data Science and Analytics COE is responsible for leading the creation and development of the overall strategy and direction of data science and advanced analytics at CDW – including ensuring continuity and seamless extension of existing programs, the development of a short- and long-term vision and roadmap, and defining and institutionalizing the role that data and analytics play throughout the organization as the fuel that drives and shapes CDW’s priorities and serves as an accelerant for CDW’s progress.
The Sr Principal ML Architect will play a key role in internal and external data science and AI products and advisory services. The use cases include real time provisioning of insights leveraging unstructured data systems as well as big data systems with complex reporting and business intelligence requirements. This role will help evaluate and improve existing data structures and play a crucial role in creating evolutionary models for current and future products This role.
This role will be the Subject Matter Expert for designing machine learning solutions that leverage various leveraging Data Science, Machine Learning and Advanced ML Engineering techniques. This role will partner with Sales, Marketing, Technology and the ML Service teams to enable data migration and rapid adoption of Machine learning services. This role will develop the reference frameworks and share best practices with the enterprise development network. This architecture will form the central platform which the data analysts, data engineers and data scientists will work in their day to day activities to generate value from all the data that they analyze.
Key Areas of Responsibility
- Build cross-functional relationships with Business Stakeholders, Architects, Data Scientists, Product Managers and IT to understand data needs and deliver on those needs.
- Drive the design, building and launching of new data models and data pipelines in production.
- Identify the sales, marketing and customer service requirements through discovery meetings.
- Design, Implementation and continue to refine CRM implementation standards, tools, customizations, plugins, and integrations.
- Manage the development of data resources and support new product launches.
- Lead discussion of product-oriented analysis in meetings with clients and partners; comfortable speaking to executives.
- Act as a sounding board on testing, experimentation, target audience profiling and consumer insights that analyze the relationship between customers, products, partners, conversions, engagement and revenue and drivers.
- Primary data liaison for stakeholders to drive transformation and to democratize use of data.
- Sunset multiple redundant warehouses and marts with significant cost savings and support new integration and modernization.
- Support compliance and auditing through a single gateway for data exchange.
- Stay abreast of technology development in retail and other industries.
- Work with multiple complex and disparate datasets to enable data delivery through various means and APIs to evaluate performance and amalgamate information to derive strategic insights and recommendations.
- Contribute and support the development of the overall data science and machine learning strategy and roadmap.
- Establish the core data foundation and common data lake to enable data driven decisions.
- Support delivery of scalable data products.
- Actively participate in the industry externally through internet research, white papers, or conferences.
Education and/or Experience Qualifications
- Bachelors or Master’s degree in computer science, Information Systems OR equivalent IT knowledge/experience.
- 10+ years of relevant work experience as a ML Engineering Architect/Data Architect/ Engineer/ Integration.
Other Required Qualifications
- Strong familiarity with data governance, data lineage, data processes, DML, and data architecture control execution
- Experience working in Data Architecture, engineering and ETL teams, managing Design, Implementation of projects that utilize big data, advanced analytics and machine learning technologies.
- Experience with agile software development methodologies.
- Ability to manage onshore and offshore resources.
- Research, design, implement, and support data pipelines\ETL using a variety of tools, NoSQL/cloud.
- Strong understanding of data and information architecture, including experience with Big Data, Relational databases, NoSQL, streaming and batch data processing.
- Strong experience building end-to-end data view with focus on integration.
- Ability to effectively present information, interact with, and respond to questions from managers, employees, customers, and vendors.
- Demonstrated experience in teaching and/or mentoring professionals.
Data Science and Advanced Analytics Required Qualifications
- Data science experience wrangling data, model selection, model training, modeling validation and deployment at scale.
- Data modeling experience, working with (RDBMS, NoSQL, Graph, Columnar, Document) and developing solutions for cloud-based data platforms.
- Hands-on experience Design, implement data solutions using technologies such as:
- Database Systems: MS SQL Server 2017, 2016, Sybase IQ, Oracle 10g
- Data Integration: SSIS, DTS, Alteryx, Talend, Azure Data Factory, Event Hub.
- Data Management: MS SQL Server Master Data Services (MDS), Collabra DGC, Atlas, Azure Data Explorer.
- CRM Systems: Microsoft Dynamics 365, Salesforce.
- Business Intelligence Systems: SSAS, Reporting Services, Excel, Pyramid, Power BI, Tableau, Qlik. Azure Streaming Analytics, Data Lake Analytics, Azure Time Series Insights, Azure Synapse Analytics.
- Bigdata Hadoop Systems: Hive, Spark, HDFS, MapReduce, TEZ
- NoSQL Systems: MongoDB, HBase, Redis, Cassandra, Couchbase, HDInsight, Elasticsearch, Azure Cosmos DB.