Stanley Black and Decker (SBD) is committed to deep and ongoing investment in Data & Analytics capability. SBD believes that advanced analytics using massive data, while already important to our business, will increasingly become fundamental – even transformational – to the value we deliver to our customers and shareholders.
SBD is seeking a Data Scientist who will be responsible for collecting data and developing insights related to innovative new business initiatives at Stanley Black & Decker focused on the digital enablement of work sites and the Internet of Things.
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 3+ 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 machine learning techniques to 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