Data Scientist – Demand Forecasting

About The Role

As a Data Scientist – Demand Forecasting, you will make an impact by developing, optimizing, and operationalizing advanced forecasting models that support strategic business planning across North America. You will be a valued member of the Data Science team and work collaboratively with business stakeholders, data engineers, analytics teams, and technology partners to drive forecast accuracy and actionable insights.

Responsibilities

• Develop, enhance, and deploy demand forecasting models to support business planning and decision-making.
• Improve forecast accuracy, reduce bias, and drive consistency across multiple markets and business segments.
• Support quarterly forecasting cycles through model validation, business reviews, and stakeholder engagement.
• Perform model experimentation, testing, monitoring, and ongoing performance optimization.
• Build scalable data science solutions using Python, PySpark, Databricks, and cloud-based technologies while maintaining efficient data pipelines and documentation.

Requirements

• Proven experience developing and deploying production-grade Data Science and Machine Learning solutions.
• Strong hands-on experience with Databricks, including PySpark, SQL, and Delta Lake.
• Advanced proficiency in Python for data science, analytics, and integration with APIs and external services.
• Experience building and orchestrating data pipelines using Azure Data Factory (ADF).
• Strong understanding of cloud-based data platforms, preferably within the Microsoft Azure ecosystem.
• Experience working with large-scale datasets and distributed data processing frameworks.
• Knowledge of CI/CD practices for Databricks deployments and releases.
• Experience with Azure DevOps and/or GitHub Actions for automation and deployment workflows.
• Strong analytical, problem-solving, and independent decision-making capabilities.
• Excellent communication skills with the ability to engage effectively with both technical and business stakeholders.

Qualifications

• Experience supporting demand forecasting, supply chain planning, or sales forecasting initiatives.
• Knowledge of scenario modeling, hierarchy reconciliation, and long-range forecasting methodologies.
• Experience monitoring model performance and implementing continuous model improvement strategies.
• Familiarity with MLOps best practices and model operationalization in enterprise environments.
• Able to translate complex technical concepts into business-friendly insights and recommendations.

Skills

• Python
• Databricks
• PySpark
• SQL
• Delta Lake
• Azure Data Factory (ADF)
• CI/CD practices
• Azure DevOps
• GitHub Actions

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Pay

The annual salary for this position is between $115,000 - $130,000 depending on experience and other qualifications of the successful candidate.

Schedule

This is a hybrid position requiring 2–3 days per week in a client or Cognizant office in Plano, Texas. Based on the business requirements of the project you are engaged in, as well as business and client requirements, the working arrangements for this role may change.