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Role Description

This role offers the opportunity to shape next-generation pricing strategies in a high-growth, technology-driven environment. You will work with large-scale datasets to uncover insights, build enterprise-grade machine learning models, and develop algorithms that directly influence pricing decisions across multiple markets. Operating at the intersection of data science, engineering, and business strategy, you will collaborate cross-functionally to deliver actionable insights that optimize revenue and customer experience. This is a highly visible role, offering significant ownership over complex pricing challenges, where your models and analyses will directly impact financial performance. Ideal candidates thrive in fast-paced environments, enjoy tackling complex problems, and are excited by the chance to translate advanced analytics into measurable business outcomes.

• Develop advanced pricing models and algorithms using statistical and machine learning methods to inform strategic decisions and optimize revenue.
• Analyze large-scale pricing datasets to identify trends, benchmark performance, and provide actionable insights across regions and business units.
• Architect core pricing intelligence systems, ensuring enterprise-grade reliability, interpretability, and regulatory compliance.
• Collaborate cross-functionally with engineers, analysts, and business teams to uncover pricing opportunities and implement data-driven strategies.
• Design and execute experiments, including A/B testing and causal inference, to validate model assumptions and measure business impact.
• Communicate insights effectively to stakeholders and leadership, translating complex data into clear, actionable recommendations.
• Drive business impact by continuously iterating on models and pricing strategies in a fast-paced, high-growth environment.

Qualifications

• 7+ years of hands-on experience in Data Science, Machine Learning, or ML Engineering, ideally in pricing, revenue optimization, or related domains.
• Strong technical skills in Python and SQL; experience with cloud-based or agnostic tech stacks; familiarity with Snowflake or Streamlit is a plus.
• Advanced statistical and machine learning expertise, including experience with large, complex datasets and model interpretability.
• Master’s degree in a quantitative field required; PhD preferred.
• Ability to translate technical insights into strategic recommendations that impact pricing and revenue.
• Excellent communication skills to present findings to both technical and non-technical audiences.
• Thrives in high-growth environments, embraces ambiguity, and is driven by measurable business impact.

Requirements

• 7+ years of hands-on experience in Data Science, Machine Learning, or ML Engineering, ideally in pricing, revenue optimization, or related domains.
• Strong technical skills in Python and SQL; experience with cloud-based or agnostic tech stacks; familiarity with Snowflake or Streamlit is a plus.
• Advanced statistical and machine learning expertise, including experience with large, complex datasets and model interpretability.
• Master’s degree in a quantitative field required; PhD preferred.
• Ability to translate technical insights into strategic recommendations that impact pricing and revenue.
• Excellent communication skills to present findings to both technical and non-technical audiences.
• Thrives in high-growth environments, embraces ambiguity, and is driven by measurable business impact.

Benefits

• Competitive base salary: $144,500—$247,600 USD, with variable pay, bonuses, and potential equity.
• Comprehensive healthcare coverage including medical, dental, and vision.
• Flexible work environment: hybrid or fully remote options depending on role requirements.
• Professional development opportunities to grow skills and advance your career.
• Supportive and innovative team culture fostering collaboration, creativity, and high impact.
• Additional perks: wellness programs, office resources, and tools to maximize productivity and work-life balance.