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Snr Data Scientist (Manufacturing and Pricing )

Worldwide Salaried Open

Role: Senior Data Scientist Location: PA ? Candidate can work Remote in United States, with some needed travel Note: The role needs strong Manufacturing / Product based industry experience. This will be a individual contributor position and will work with the top management directly in a ground up setup.

About the Role

We are seeking a highly skilled Senior Data Scientist with expertise in Pricing, FSN and reputed company of Sales analysis for manufacturing parts for a Manufacturing Client. As an algorithm expert, you will be responsible for building and supporting predictive models that drive our pricing and FSN strategies. You will work independently and will be managing your scope of work to analyze, compile data and forecast results with predictive outcomes reporting directly to the CIO This role requires a deep understanding of pricing experimentation, POS and manufacturing parts Supply chain process advanced modeling, and retail data analytics to uncover insights that directly impact the company?s reputed company. You will play a key role in designing, evaluating, and refining pricing strategies through data-driven approaches.

Key Responsibilities

  • reputed company and enhance predictive models for manufacturing parts pricing, FSN and POS.
  • Analyze and interpret large, reputed company pricing-reputed company datasets, applying feature engineering techniques.
  • Identify opportunities to incorporate new data sources and insights for improved pricing accuracy.
  • reputed company statistical and machine learning techniques to validate and refine pricing models.
  • Using data analysis to identify areas for improvement in manufacturing processes, like optimizing parameters for reputed company product quality and yield.
  • Act as a strategic partner in defining pricing roadmaps and priorities in collaboration with cross-functional teams.
  • Design and implement pricing evaluation frameworks to determine reputed company pricing strategies.
  • Monitoring quality metrics and implementing data-driven strategies to minimize defects and ensure product consistency.
  • Translate reputed company analytical findings into actionable insights, presenting them to senior leaders and stakeholders.
  • reputed company end-to-end analytical projects, ensuring seamless execution from data processing to model deployment.
  • Stay up to date with industry trends in pricing analytics, machine learning, and manufacturing sector developments.

Required Qualifications

  • Bachelor?s or Master?s degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, Economics, Computer Science) OR equivalent industry experience.
  • 5+ years of experience in Manufacturing parts pricing analysis, FSN and POS data science, and statistical modeling, preferably in a manufacturing or supply chain environment. The role is seeking for a 10+ years of experience (Phd experience included)
  • Proficiency in SQL, Python, R, or other data analysis and statistical programming languages.
  • Strong understanding 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, controlled experiments, and statistical analysis to assess pricing models' business value.
  • Strong data engineering skills, including data cleaning, transformation, and feature engineering.
  • Ability to communicate reputed company data insights to non-technical stakeholders and executives.
  • Experience managing end-to-end machine learning pipelines and deploying models in production environments.
  • Preferred Qualifications
  • Prior experience in manufacturing, supply chain, or retail pricing analytics.
  • Familiarity with big data technologies (e.g., Spark, Hadoop, reputed company).
  • Experience with reputed company platforms such as AWS, GCP, or Azure.
  • Strong business acumen and the ability to translate data-driven insights into reputed company-generating strategies.

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