R&D Lead Data Scientist

Cleveland, OH, United States

Sherwin-Williams

No matter where you are in the world or what surfaces you are painting or coating, Sherwin-Williams provides innovative paint solutions that ensure your success.

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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.

 

Essential Functions

 

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.
  • Lead project discovery through requirements gathering, analysis, design documentation, and impact analysis for model design.
  • 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, a[SC1] nd other data visualization tools.
  • Coach peers on advanced statistical and ML techniques.

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.
Formal Education & Certification
  • 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.
  • Master’s Degree in Data Science, Computer Science, Statistics, Applied Mathematics, or other relevant discipline is preferred.
  • 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.
  • 5+ years of hands-on experience with Python language for ML and tasks.
  • 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.
  • Advanced knowledge of data analysis, cleaning, and preparation.
  • 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.

 

Interpersonal Skills and Characteristics
  • 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.
  • Is a confident, energetic self-starter, with strong interpersonal skills.
  • Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.
  • Flexibility, able to adapt to change and embrace it.
  • 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.

Here, we believe there’s not one path to success, we believe in careers that grow with you. Whoever you are or wherever you come from in the world, there’s a place for you at Sherwin-Williams. We provide you with the opportunity to explore your curiosity and drive us forward. Sherwin-Williams values the unique talents and abilities from all backgrounds and characteristics. All qualified individuals are encouraged to apply, including individuals with disabilities and Protected Veterans. We’ll give you the space to share your strengths and we want you show us what you can do. You can innovate, grow and discover in a place where you can thrive and Let Your Colors Show! 
At Sherwin-Williams, part of our mission is to help our employees and their families live healthier, save smarter and feel better. This starts with a wide range of world-class benefits designed for you. From retirement to health care, from total well-being to your daily commute—it matters to us. A general description of benefits offered can be found at http://www.myswbenefits.com/. Click on “Candidates” to view benefit offerings that you may be eligible for if you are hired as a Sherwin-Williams employee.
Compensation decisions are dependent on the facts and circumstances of each case and will impact where actual compensation may fall within the stated wage range. The wage range listed for this role takes into account the wide range of factors considered in making compensation decisions including skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.
The wage range, other compensation, and benefits information listed is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.
Sherwin-Williams is proud to be an Equal Employment Opportunity/Affirmative Action employer committed to an inclusive and diverse workplace. All qualified candidates will receive consideration for employment and will not be discriminated against based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, pregnancy, genetic information, creed, marital status or any other consideration prohibited by law or by contract.
As a VEVRAA Federal Contractor, Sherwin-Williams requests state and local employment services delivery systems to provide priority referral of Protected Veterans.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Chemistry Classification Computer Science Data analysis Data visualization Engineering Hadoop Machine Learning Mathematics ML models Model deployment Model design NoSQL NumPy Oracle Python R R&D RDKit Research Scikit-learn SciPy SQL Statistical modeling Statistics Tableau Testing Unstructured data

Perks/benefits: Career development Conferences Health care Startup environment Team events

Region: North America
Country: United States
Job stats:  3  0  0

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