Senior Data Scientist (michelinhr)

Job Description

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We are seeking a talented Senior Data Scientist of Dynamic Pricing with a passion for solving business problems through the creation and management of dynamic pricing models. In this role, you will lead the innovation and support of our dynamic pricing program, directly impacting growth, profitability, and overall efficiency. You may have the opportunity to navigate the complexities of dynamic pricing in a constantly changing market, using our rich database of millions of data points to build and maintain effective pricing strategies.  The position will also be expected to mentor 1-2 data scientists.

Key Responsibilities:

• Collaborate with a team to innovate and continuously improve dynamic pricing engine by integrating new data sources and model enhancements to optimize pricing strategies.
• Apply data science techniques including machine learning, AI, and statistical modeling across multiple functional areas of the organization to drive improved decision making
• Serve as a highly qualified technical resource to Group Pricing Transformation management team and develop trust with high quality insights and deliverables.
• Create and track accuracy and performance metrics (both technical and business metrics) of models & tools
• Create, enhance, and maintain technical documentation, and present to scientists, engineers, and business leaders
• Experience with dynamic pricing and reinforcement learning techniques
• Experience with revenue/margin optimization using AI techniques
• Familiarity with retail operations and e-merchandising strategies

Basic Qualifications :

• 5+ years of experience with data scripting languages (e.g., SQL, Python, R etc.,)e
• 3+ years of advanced algorithms experience in retail.
• At least 3 years of experience in quantitative analytics or data modeling
• Deep understanding of predictive modeling, machine learning, clustering and classification techniques, and algorithms
• Familiarity with coding frameworks and visualization tools ( PySpark)