Data Scientist

3 days ago

Portland, United States CorSource Full time

Role Overview:

The Demand Planning and Forecasting Data Scientist independently plans, schedules, and leads data and analytics projects focused on demand forecasting within the manufacturing supply chain. This role is responsible for developing predictive models and machine learning algorithms, maintaining the analytics environment, and executing data integration and analysis using Python, SQL, Azure, and Snowflake. The position also includes data engineering responsibilities, such as designing, implementing, testing, deploying, and maintaining stable, secure, and scalable data solutions and pipelines. Collaboration with the Data & Analytics and other development teams is essential to define requirements, mine and analyze data, and deploy high-quality models that support the organization’s forecasting needs.


Role Responsibilities:

  • Proposes innovative solutions and strategies to address demand planning challenges; works independently on complex forecasting problems by adapting standard analytics and data science techniques.
  • Designs, implements, tests, deploys, and maintains secure and scalable data engineering solutions and pipelines to support demand planning projects, including integrating diverse data sources into the central data warehouse.
  • Undertakes preprocessing of structured, semi-structured, and unstructured data to prepare it for analysis.
  • Analyzes large datasets to uncover trends and patterns relevant to demand forecasting.
  • Builds and optimizes predictive models and machine-learning algorithms tailored to demand forecasting needs.
  • Selects features, constructs, and optimizes classifiers using advanced machine learning techniques.
  • Combines models through ensemble modeling to enhance forecasting accuracy.
  • Collaborates with engineering and product development teams to deliver actionable insights through predictive analytics.
  • Performs data mining utilizing state-of-the-art methodologies.
  • Analyzes demand planning and BI issues to identify suitable solutions; organizes design reviews with peers and project leads, ensuring comprehensive documentation for all projects.
  • Responsible for thoroughly testing data, analytics, and machine learning solutions to ensure reliability and accuracy.
  • Works with minimal supervision on most projects, with closer oversight on new tasks.


Qualifications:

  • At least 10 years of experience in data science, with a strong focus on demand forecasting in a manufacturing or supply chain context.
  • Proven track record of applying data science techniques to solve complex demand-related problems.
  • Strong knowledge of Python, with at least 5 years of experience, including expertise in libraries such as Pandas and NumPy for data preparation and analysis.
  • In-depth expertise in Snowflake for data warehousing and analytics.
  • Strong command of SQL and familiarity with ETL best practices for data manipulation and transformation.
  • Comprehensive understanding of machine learning algorithms and frameworks (e.g., TensorFlow, Scikit-learn) as they relate to predictive modeling.
  • Experience leading projects and mentoring junior data scientists or analysts.
  • Ability to work with structured, semi-structured, and unstructured data to develop and deploy predictive models and machine learning solutions.
  • Strong analytical skills to interpret complex data requirements and apply advanced analytics methodologies effectively.
  • Demonstrated skill in using APIs for data integration from various systems and platforms.
  • Excellent problem-solving abilities, with strong interpersonal and communication skills to collaborate effectively within a team.


Preferred Qualifications:

  • Experience with Azure services and applications related to data science and analytics.
  • Familiarity with Snowflake features, including Snowpark and Cortex, for data solutions.
  • General understanding of business analysis best practices and their application in manufacturing environments.
  • Experience developing cloud-based data warehouses (e.g., Snowflake or Databricks).
  • Knowledge of lambda and kappa architectures, as well as iPaaS platforms and low-code/no-code solutions.

This role offers an exciting opportunity for a skilled data scientist passionate about driving demand planning and forecasting excellence within a leading manufacturing organization.

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