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Data Scientist
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Data Scientist I
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R&D Lead Data Scientist
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Sherwin-Williams Cleveland, United StatesThe Lead Data Scientist is part of the Enterprise Advanced Analytics & AI team within the Enterprise Data & Insights organization. · The Lead Data Scientist will play a pivotal role in data discovery, connecting datasets, data wrangling, building models, and model deployment for ...
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R&D Lead Data Scientist
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The Sherwin-Williams Company Cleveland, United StatesThe Lead Data Scientist is part of the Enterprise Advanced Analytics & AI team within the Enterprise Data & Insights organization. · The Lead Data Scientist will play a pivotal role in data discovery, connecting datasets, data wrangling, building models, and model deployment for ...
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Data Scientist
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Data Scientist Associate
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Data Scientist Associate
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Data Scientist Associate
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Product Development Scientist
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R&D Lead Data Scientist - Cleveland, United States - The Sherwin-Williams Company
Description
The Lead Data Scientist is part of the Enterprise Advanced Analytics & AI team within the Enterprise Data & Insights organization.
The Lead Data Scientist will play a pivotal role in data discovery, connecting datasets, data wrangling, building models, and model deployment for the R&D organization.
This position is an excellent opportunity for an individual to contribute to the digital initiatives and data science projects supporting R&D.
The Lead Data Scientist will focus on staying up to date with available modeling and analytical techniques and ensuring the appropriate techniques are applied to R&D initiatives.
The R&D Data Scientist will utilize a combination of IT skills, data skills, analytics skills, and chemistry subject matter expertise.
Role will engage and have regular discussions with other data scientists, data analysts, chemists, scientists, and internal customers to successfully move a given project forward.
Problem Analysis and Project Management
Collaborate with chemists and material scientists on methods and processes to create and manage experimental results using FAIR data principles.
Participate in establishing the technical approach for integrating scientific knowledge, formulation science, and machine learning methods to accelerate the development of coatings.
Understand business needs, determine data/model usage goals, and create project plans.
Plan and organize tasks, report progress, and coordinate with other team members.
Identify opportunities to create data-driven ML models in R&D.
Identify, lead the implementation of, and validate appropriate statistical/ML models for specific projects in the R&D organization.
Data Exploration and Preparation
Apply statistical analysis, machine learning, and visualization techniques to various types of data. Test hypotheses using various quantitative methods.
Display drive and curiosity to understand the business process to its core.
Network with R&D experts to better understand the mechanics that generate data in R&D.
Network with external functional areas to connect and join lab generated data to enterprise data sets.
Perform data discovery and wrangling to run models utilizing experience in data extraction and data pre-processing and manipulation.
Machine Learning
Apply various ML and advanced analytics techniques to perform classification or prediction tasks.
Apply chemical and materials domain knowledge to develop models that accelerate the development of new formulations.
Testing of ML models, such as cross-validation and new data collection.
Keep team appraised of developments in machine learning/AI/statistical research literature that may be of practical use in R&D.
Design and Deployment
Develop, debug, refine, deploy, and maintain analytical models using Python (including SimPy, SciPy, SciKit, RDKit, NumPy, and other data science and data visualization libraries in Python), R, and other software development and data science tools, including maintaining and updating existing models.
Develop, deploy, and maintain visualizations and interactive reporting/analytics tools for analytical models using Python, Tableau, Visual Components, and other data visualization tools.
Other
Train and mentor other R&D staff on data science principles and techniques.
Train peers on specialist data science topics.
Network with internal and external partners.
Upskill yourself (through conferences, publications, courses, local academia, and meetups).
Promote collaboration with other teams within the organization. Encourage reuse of artifacts.
Incidental Functions
Evaluate data services and products:
Perform product proof of concept analysis.
Assists with various projects as may be required to contribute to the efficiency and effectiveness of the work.
Participate in hiring activities and fulfilling affirmative action obligations and ensuring compliance with the equal employment opportunity policy.
Individual's in-office time will be spent split between the R&D facility and working with other members of the Enterprise Advanced Analytics & AI Team.
Bachelor's degree (or foreign equivalent) in a Computer Science, Computer Engineering, or Information Technology field of study (e.g., Information Technology, Electronics and Instrumentation Engineering, Computer Systems Management, Mathematics) or equivalent experience.
Significant coursework, training, or experience in Chemistry/Materials Science/Polymer Science or similar discipline preferred.
Knowledge & Experience
8+ years total Data Science/IT experience.
5+ years of hands-on experience with statistical modeling, machine learning, and artificial intelligence preferably in chemistry, formulation science and/or materials science.
2+ years of hands-on experience with R statistical language.
Database and programming languages experience and data manipulation and integration skills using SQL, Oracle, Hadoop, NoSQL Databases, or similar tools.
Proven ability in using exploratory analysis and preparing unstructured data to draw conclusions.
Experience designing experiments through statistical approaches such as Design of Experiments or other techniques.
Strong ability to work with both IT and R&D in integrating analytics and data science output into business processes and workflows.
Excellent verbal and written communications.
Highly responsive and alert to new learning opportunities, growth, and development of technical, interpersonal and business skills.
Motivated to develop objectives and timelines to accomplish goals.
Strong experience supporting and working with cross-functional teams in a dynamic business environment.
Strong collaboration experience with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly.
Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.
Strong commitment to inclusion and diversity.
This position is not eligible for sponsorship for work authorization now or in the future, including conversion to H1-B visa.
This position works in the office three days a week and is eligible to work remotely two days a week.
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