Lead Data Scientist

About the Role

Blend360 is seeking a highly skilled Lead Data Scientist with specialized experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate possesses a robust background in Statistics and Machine Learning, with a strong emphasis on Bayesian modeling. As a key member of our Data Science team, you will collaborate closely with clients to develop sophisticated pricing strategies. You will leverage cutting-edge tools and techniques, including AWS SageMaker, to enhance business outcomes.

Key Responsibilities

• Lead and contribute to the development of pricing optimization models, utilizing statistical and machine learning techniques to inform strategic decisions.
• Analyze pricing elasticity to forecast consumer reactions to price changes, assisting clients in maximizing revenue and market share.
• Implement and deploy machine learning models using AWS SageMaker for scalable and efficient cloud-based performance.
• Apply Bayesian modeling to support decision-making, providing insights into model uncertainty and predictions.
• Collaborate with cross-functional teams to integrate data-driven insights into business processes.
• Clearly and concisely communicate complex findings to both technical and non-technical stakeholders.
• Continuously research and experiment with new modeling approaches and tools to enhance the accuracy and efficiency of pricing solutions.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Economics, or a related quantitative field. Advanced degrees are preferred.
• A minimum of 7 years of hands-on experience in data science, with a specific focus on pricing optimization and elasticity modeling.
• Expertise in Bayesian modeling and various machine learning techniques.
• Demonstrated experience using AWS SageMaker for model development, deployment, and monitoring.
• Familiarity with the AWS Certified Data Analytics – Specialty certification is a plus.
• Strong programming proficiency in Python (preferred) or R.
• Experience with cloud platforms, particularly AWS, including hands-on use of SageMaker.
• Proficiency with statistical analysis tools and libraries such as NumPy, Pandas, PyMC3, or similar.
• Exceptional problem-solving and analytical thinking capabilities.
• Ability to thrive in a fast-paced environment and manage multiple concurrent projects.
• Excellent communication skills, with the ability to articulate complex concepts to diverse audiences.

Preferred Qualifications

• Experience with A/B testing, econometrics, or other statistical experimentation methodologies.
• Familiarity with other cloud computing platforms like Azure or GCP.
• Experience working within cross-functional teams and in client-facing roles.

Additional Information

• Opportunity to engage with cutting-edge technology in a dynamic work setting.
• Exposure to a wide array of industries and diverse projects.
• A collaborative and inclusive work environment that promotes growth and professional development.