Joining the Stanley Black & Decker (SBD) team means joining one of the world's largest, fastest-growing, and most dynamic companies. SBD, a Fortune 200 company is a world-leading provider of tools and storage, commercial electronic security and engineered fastening systems, with unique growth platforms and a track record of sustained profitable growth. We have been globally recognized as one of the most innovative, sustainable, and rewarding companies in the world.
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.
Stanley Black & Decker is looking for a Principle Manufacturing Data Scientist to join their Advanced Manufacturing Center of Excellence team. Since 1843, Stanley Black and Decker has been committed to innovation and social responsibility, while becoming a leader in multiple industries. In this position, one can expect to use their expertise in big data and advanced analytics to lead others to solve critical business problems. The role combines strong data science capabilities with a rigorous understanding of the use cases, nuances and challenges of deploying advanced analytics in a manufacturing environment.
Essential Job Functions
A clear focus on delivering sustainable value to SBD's manufacturing plants at scale and speed.
Leverage big data, process knowledge, statistics and data science to discover patterns and solve strategic & tactical business problems using structured and unstructured data sets of varying size and contexts across multiple environments.
Take part in and lead value discovery workshops at SBD locations globally to identify potential use cases that drive improvements through analytics.
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 manufacturing, Industry 4.0 and IIoT.
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 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 linear & logistic regression, multivariate statistical analysis, statistics, 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 experience with Cloud based HaaS/PaaS solutions such as MS Azure, AWS EMR
Strong knowledge of analysis tools such as Python, R, MATLAB, Spark or SAS.
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
A strong understanding of data profiling and data cleansing techniques.
Familiarity with working with manufacturing, time-series potentially autocorrelated data.
Understanding of the strengths and weaknesses of AI technologies such as neural networks and machine learning particularly when applied to manufacturing data sets.
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
Depth in relevant field(s) for data science, including:
Statistical Analysis & Modeling
Machine Learning Algorithms & Techniques
Deep Learning / Neural Networks
Understanding Business Problems
Data Wrangling & Exploration
Problem Solving Mindset
All qualified applicants to Stanley Black & Decker are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran's status or any other protected characteristic.
Stanley Black And Decker