Job Title: Data Scientist
The Data Science team within Catalyst Brands “Data and Analytics” team is a cross-functional team that solves complex problems across various functional areas. As a Data Scientist in our data science team, you will leverage your technical skills, business acumen, and creativity to extract and analyze massive data sets and translate complex findings in a structured and clear manner to a non-technical audience.
Responsibilities:
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Collaborate with partners and decision makers across multiple business functions to identify opportunities to add value using analytics. Areas cover marketing, digital, store operations, supply chain, and other operational functions in retail.
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Help define business objectives and translate the business questions into analytical questions, ideate and develop solutions with advanced analytics concepts and techniques
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Build proof-of-concept analyses and models with clearly defined and measurable success metrics to demonstrate value and feasibility
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Lead the scaling and operationalization of analytical solutions ensuring capture of intended value at enterprise level
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Share concepts and insights clearly with business partners through visualizations
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Work with partners in IT throughout the solution development process from data acquisition to implementation of decision systems.
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Evangelize data science by sharing the art of the possible with the business community
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Add to existing best practices in data science and champion adoption of best practices across the organization
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Keep current with retail analytics landscape and help create value at Catalyst Brands using the knowledge
Qualifications:
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A Master’s degree in Engineering, Statistics, Physics, or a related discipline, along with a minimum of 4 years of analytical experience — including at least 2 years in core data science — is required.
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Good understanding of common machine learning algorithms including regression, classification, neural networks, etc. with experience in real world applications of these algorithms
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Experience with data and feature engineering to support various analytical approaches
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Strong database experience with advanced SQL skills
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Ability to work with data on distributed platforms (like Hadoop) using tools such as Hive
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High proficiency in using tools like R and Python for data science activities
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Proficiency with data visualization tools, such as Tableau, R Shiny, MicroStrategy, etc.
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Strong understanding of data infrastructure (cloud and non-cloud)
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Research publications are a plus but not required
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Knowledge of GenAI models/Tools are a plus but not required
