About the Position
We are looking for a Senior Data Scientist with specialized knowledge in pricing, FSN, and point-of-sale analysis for manufacturing parts. As a subject matter expert in algorithms, you will create and maintain predictive models that inform our pricing and FSN strategies. This role offers independence, allowing you to manage your workload, analyze data, and forecast results, with direct reporting to the Chief Information Officer (CIO).
The ideal candidate will have a solid understanding of pricing experiments, point-of-sale systems, manufacturing part supply chains, and retail data analytics. This position plays a crucial role in enhancing data-driven pricing strategies that impact the company's financial performance.
Key Responsibilities:
- Develop and refine predictive models to optimize pricing, FSN, and POS strategies for manufacturing parts.
- Analyze and interpret complex pricing datasets, utilizing advanced feature engineering techniques.
- Identify new data sources and insights to improve pricing accuracy.
- Apply statistical and machine learning methods to validate and improve pricing models.
- Use data analysis to identify manufacturing process improvements, such as optimizing production parameters for higher quality and yield.
- Collaborate with cross-functional teams to define pricing strategies and priorities.
- Design and implement frameworks for pricing evaluations to determine the best pricing approaches.
- Monitor quality metrics and execute data-driven strategies to reduce defects and maintain consistency.
- Communicate complex analytical findings clearly to senior leadership and key stakeholders.
- Lead analytical projects from data processing to model deployment, ensuring smooth execution.
- Stay informed about industry trends in pricing analytics, machine learning, and manufacturing advancements.
Required Qualifications:
- Bachelor's or Master's degree in a quantitative discipline (e.g., Data Science, Statistics, Mathematics, Economics, Computer Science), or equivalent professional experience.
- Over 5 years of experience in pricing analysis for manufacturing parts, FSN, POS data science, and statistical modeling (10+ years of experience preferred, including PhD-level expertise).
- Proficiency in SQL, Python, R, or other programming languages for data analysis and statistical modeling.
- Strong knowledge of pricing strategies, price elasticity modeling, and demand forecasting.
- Expertise in machine learning techniques (supervised/unsupervised learning, classification, regression, etc.).
- Experience with A/B testing, experimental design, and statistical analysis to assess the business value of pricing models.
- Strong skills in data engineering, including data cleaning, transformation, and feature engineering.
- Ability to communicate complex data insights effectively to non-technical stakeholders and executives.
- Experience in managing end-to-end machine learning pipelines and deploying models in production environments.
Preferred Qualifications:
- Experience in manufacturing, supply chain, or retail pricing analytics.
- Familiarity with big data technologies
- Experience working with Azure.
- Strong business sense, with the ability to translate data insights into actionable revenue-generating strategies.
About the Position
We are looking for a Senior Data Scientist with specialized knowledge in pricing, FSN, and point-of-sale analysis for manufacturing parts. As a subject matter expert in algorithms, you will create and maintain predictive models that inform our pricing and FSN strategies. This role offers independence, allowing you to manage your workload, analyze data, and forecast results, with direct reporting to the Chief Information Officer (CIO).
The ideal candidate will have a solid understanding of pricing experiments, point-of-sale systems, manufacturing part supply chains, and retail data analytics. This position plays a crucial role in enhancing data-driven pricing strategies that impact the company's financial performance.
Key Responsibilities:
- Develop and refine predictive models to optimize pricing, FSN, and POS strategies for manufacturing parts.
- Analyze and interpret complex pricing datasets, utilizing advanced feature engineering techniques.
- Identify new data sources and insights to improve pricing accuracy.
- Apply statistical and machine learning methods to validate and improve pricing models.
- Use data analysis to identify manufacturing process improvements, such as optimizing production parameters for higher quality and yield.
- Collaborate with cross-functional teams to define pricing strategies and priorities.
- Design and implement frameworks for pricing evaluations to determine the best pricing approaches.
- Monitor quality metrics and execute data-driven strategies to reduce defects and maintain consistency.
- Communicate complex analytical findings clearly to senior leadership and key stakeholders.
- Lead analytical projects from data processing to model deployment, ensuring smooth execution.
- Stay informed about industry trends in pricing analytics, machine learning, and manufacturing advancements.
Required Qualifications:
- Bachelor's or Master's degree in a quantitative discipline (e.g., Data Science, Statistics, Mathematics, Economics, Computer Science), or equivalent professional experience.
- Over 5 years of experience in pricing analysis for manufacturing parts, FSN, POS data science, and statistical modeling (10+ years of experience preferred, including PhD-level expertise).
- Proficiency in SQL, Python, R, or other programming languages for data analysis and statistical modeling.
- Strong knowledge of pricing strategies, price elasticity modeling, and demand forecasting.
- Expertise in machine learning techniques (supervised/unsupervised learning, classification, regression, etc.).
- Experience with A/B testing, experimental design, and statistical analysis to assess the business value of pricing models.
- Strong skills in data engineering, including data cleaning, transformation, and feature engineering.
- Ability to communicate complex data insights effectively to non-technical stakeholders and executives.
- Experience in managing end-to-end machine learning pipelines and deploying models in production environments.
Preferred Qualifications:
- Experience in manufacturing, supply chain, or retail pricing analytics.
- Familiarity with big data technologies
- Experience working with Azure.
- Strong business sense, with the ability to translate data insights into actionable revenue-generating strategies.