Senior Data Scientist

The Senior Data Scientist specializes in developing and programming methods, processes, and systems to consolidate and analyze structured, unstructured and/or diverse "big data" sources to generate insights and solutions. This involves identifying insights from data, interpreting and communicating findings to management. By using statistical analysis, Machine Learning (ML) techniques, and data visualization, the Senior Data Scientist will uncover patterns and trends within data to help the business make informed decisions and solve complex problems.

Responsibilities:

• Analyze large amounts of complex data to extract insights and drive decision-making through data visualization tools and presentation.
• Design, develop and program methods, processes, and systems to consolidate and analyze structured, unstructured, and diverse “big data” sources to generate actionable insights and solutions for Sherwin-Williams PSG and CBG marketing groups.
• Interact with marketing teams to identify questions and issues for data analysis and experiments.
• Understand and apply key business concepts, strategies, and practices to effectively analyze how data aligns with business objectives and impacts decision-making processes.
• Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to marketing and business managers.
• Develop statistical models, machine learning algorithms, and predictive analytics solutions to address business challenges.

Skills & Experience

Required

• Bachelor’s degree in Data Science, Marketing Analytics, Statistics, Math, Business Analytics, or related field, or in lieu of related degree, at least 7 years of experience in AI, Data Science, or related field

Preferred

• MBA or Graduate-level degree
• Related certifications (e.g., Machine Learning, Artificial Intelligence) preferred

Knowledge & Experience

• 7 years of experience in AI, Data Science, or related field
• Knowledge of machine learning algorithms, statistical models, and data mining techniques
• Experience in designing and implementing data-related AI solutions for complex business problems
• Excellent communication and stakeholder management skills, with the ability to present technical ideas and results to non-technical audiences

Technical Skills

• Programming Languages (e.g., Python, R)
• AI and Machine Learning Frameworks (e.g., Scikit-learn, H2O, Dataiku)
• Cloud Computing Platforms: (e.g., AWS, Azure, GCP)
• Database Technologies (e.g., SQL, Spark)
• Data Visualization Tools (e.g., Tableau, Power BI)
• Prompt Engineering
• AI and Machine Learning Frameworks (e.g., TensorFlow, Keras, PyTorch)
• Database Technologies (e.g., NoSQL, Hadoop)