Data Scientist – Demand and Supply Planning

• Develops algorithms and applications, performs large scale experimentation, builds data driven apps to translate data into intelligence, and develops solutions for solving business problems using coding
• Incorporates predictive modeling, statistics and other analysis techniques for collecting, exploring, interpreting and extracting insights from structured and unstructured data
• Organizes, interprets and structures insights from data, detects data anomalies and makes corrections
• Performs descriptive statistical analysis, develops visualizations, applications, dashboards, or presentations and communicates insights in a clear and effective way to help the organization with better decision-making
• Supports troubleshooting service offerings using proprietary analytical platforms, commercial tools and custom scripts
• Drives the design, development and optimization

Qualifications

• You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications:

• The candidate must have a bachelor''s degree in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 6+ years of experience -OR- a master''s degree in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 4+ years of experience -OR- a PhD in Computer Engineering, Computer Science, Information Technology or other Engineering related field and 2+ years of experience in:
• Demand Forecasting and Demand Planning transformation Sales Forecasting, Statistical forecasting, system-driven disaggregation, Sales and Operations Planning.
• Process transformation experience within a larger program Requirements gathering, systems/business analysis, process mapping, solution acceptance testing and deployment.
• Designing and deploying solutions using enterprise planning software solutions such as SAP IBP, Blue Yonder, JDA DM, i2, Kinaxis, SAP BPC, Anaplan, Demantra, SAP APO or equivalent.
• Product backlog, feature definition, requirements analysis, functional design/specifications, solution delivery, testing, user training, TCM (transition change management).

Key Responsibilities:

• Develop predictive and machine learning models for demand forecasting and supply optimization.
• Perform data wrangling, feature engineering, and statistical analysis on large, complex datasets.
• Work with enterprise demand planning solutions (Blue Yonder, SAP, or equivalent) team and learn processes to optimize Build interactive dashboards and visualizations for real-time insights using visualization tools (Power BI/Tableau).
• Apply advanced data science techniques including time-series forecasting, regression, classification, clustering, and optimization algorithms.
• Develop and validate models using Scikit-learn, TensorFlow, or PyTorch for predictive analytics and scenario planning.
• Implement automated pipelines for data ingestion, model training, and deployment in cloud environments (Azure/AWS).Collaborate with teams to define requirements, create user stories, and support UAT.

Qualifications

• BTech/B.E/BS/MS in Computer Science, Data Science, or related field.5+ years in data science applications for supply chain.
• Expertise in Python, R, SQL (Snowflake), and libraries like Pandas, NumPy, Scikit-learn, TensorFlow/ PyTorch .
• Strong knowledge of forecasting techniques, time-series modeling, regression, classification, clustering, and optimization algorithms.
• Experience with big data platforms and distributed computing frameworks Hands-on experience with data visualization tools (Power BI, Tableau) and dashboard development.
• Experience with Agile methods and tools (Jira, Rally).

Preferred

• Blue Yonder or equivalent applications (SAP, Kinaxis, O9) Planning experience.
• Semiconductor/high-tech industry background.
• Familiarity with cloud platforms (Azure/Snowflake) and data pipelines for analytics.