Stanley Black & Decker has created this state of the art manufacturing incubator to accelerate its global Industry 4.0 "smart factory" initiative across the entire organization. The 23,000-square foot facility will serve as a hub for the latest advancements in IoT, cloud computing, artificial intelligence, 3-D printing, robotics and advanced materials. This team will set the overall vision and strategy for the company's Industry 4.0 initiative and supply the resources and expertise necessary to serve as the epicenter for the latest technologies and processes with respect to Industry 4.0.
Essential Job Functions
- Leverage big data and data science to discover patterns and solve strategic & tactical business problems using massive structured and unstructured data sets across multiple environments
- Develop analytic capabilities (e.g. models and processes) that drive better outcomes for both customers and the company
- Drive the collection, cleansing, processing and analysis of new and existing data sources.
- Build, test, and deploy predictive models and/or machine learning algorithms on large static and/or streaming data sets
- Report findings by creating useful and appropriate data outputs and visualizations tailored for the intended audiences
- Learn & stay current on analytics developments in one or more business domains: Internet of Things, Manufacturing, Supply Chain, Forecasting, Marketing and Sales, Pricing, etc.
- Learn & stay current on developments in one or more analytics domains: Optimization, Machine Learning, Deep Learning / AI, Simulation, etc.
- Generate innovative ideas, establish new research directions, shape and execute the information strategy in support of technical projects and new product developments
- Work with and support other team members, management, and partners
Essential Skills & Experience
- Advanced degree (MS/PhD) in a relevant technical field (e.g., Computer Science, Mathematics, Applied Mathematics, Statistics, Operations Research, Industrial Engineering, Econometrics) with 5-8+ years' experience in related data science, analytics, and model building roles
- Experience working with large complex data sets, real time/near real time analytics, and distributed big data platforms (Hadoop & MapReduce and/or Cassandra/Spark)
- Strong practical knowledge of analytical techniques and methodologies such as machine learning/supervised and unsupervised techniques, segmentation, mix and time series modeling, response modeling, lift modeling, experimental design, neural networks, data mining and optimization techniques
- Strong knowledge of analysis tools such as Python, R, MATLAB, Spark or SAS. R/Spark on Hadoop or Cassandra preferred.
- Strong background in applying statistical and machine learning techniques to enable predictive modeling and experience with Machine Learning libraries (via R, H2O, Python, Spark, etc.)
- Proficiency in consuming REST based API (with JSON payload) is a plus.
- Fluency in big data platforms including Hadoop, MapReduce, Hive, Spark, PIG
- Familiarity with Cloud based HaaS/PaaS solutions such as AWS EMR, MS Azure.
- A strong understanding of data profiling and data cleansing techniques
- Natural curiosity and a strong passion for empirical research and problem solving
- Strong written and verbal communications skills; comfortable communicating with senior levels of both business and technology leadership