Sr Data Science Consultant II - Python, R & ML

As a Sr Data Science Consultant II, you will analyze complex data sets for demand forecasting and supply planning, applying statistical and machine learning techniques. Responsibilities include data ingestion, visualization, feature engineering, and model fine-tuning. You will implement optimization algorithms to enhance supply chain efficiency, advise stakeholders on best practices, and identify data-driven strategies for continuous improvement in supply chain management.

Must Have

• Analyze large, complex data sets related to demand forecasting and supply planning.
• Apply statistical and machine learning techniques to forecast demand.
• Perform data ingestion, data visualization, and verify data integrity.
• Conduct feature engineering and configure/fine-tune forecasting models.
• Implement optimization algorithms to improve supply chain efficiency.
• Serve as a subject matter expert for supply chain analytics.
• Identify inefficiencies and recommend data-driven strategies for continuous improvement.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Industrial Engineering, Operations Research, Supply Chain Management, or a related field.
• 5-10 years of experience in data science or Supply Chain Operations Analytics, or forecasting projects.
• Proficiency in Python, R, SQL.
• Experience with supply chain management platforms/processes.
• Good, applied statistics skills (Distributions, statistical testing, regression).
• Hands-on experience with machine learning techniques/algorithms (regression, classification, clustering) and optimization models.
• Familiarity with supply chain processes (demand forecasting, inventory management, procurement, logistics, and distribution).
• Strong problem-solving skills and analytical thinking.
• Excellent verbal and written communication skills.

Good to Have

• Experience with data visualization tools.
• Ability to work independently and as part of a team in a consulting environment.
• Attention to detail, with the ability to manage large data sets and complex analysis.

• Data Analysis & Modeling: Analyze large, complex data sets related to demand forecasting, supply planning to uncover actionable insights.
• Machine Learning: Apply statistical and machine learning techniques to forecast demand which would include
• Data ingestion, data visualization and insights, verifying the integrity of data used for analysis
• Feature engineering, configuring forecasting models
• Fine tune forecasting model
• Present results in a clear manner
• Supply Chain Optimization: Implement optimization algorithms to improve supply chain efficiency, reduce costs, and enhance service levels.
• Consulting & Advisory: Serve as a subject matter expert (SME) for supply chain analytics, advising stakeholders on best practices, tools, and strategies for effective supply chain management.
• Process Improvement: Identify inefficiencies within the supply chain and recommend data-driven strategies for continuous improvement.

What we are looking for:

• Educational Background: Bachelor’s or Master’s degree in Data Science, Computer Science, Industrial Engineering, Operations Research, Supply Chain Management, or a related field.
• Experience: 5-10 years of experience in data science or Supply Chain Operations Analytics, or worked on Forecasting projects leveraging statistical/ML models; experience with data visualization tools
• Technical Skills: Proficiency in data science tools and programming languages such as Python, R, SQL, and Experience with supply chain management platforms/processes. Good, applied statistics skills, such as Distributions, statistical testing, regression, etc
• Machine Learning: Hands-on experience with machine learning techniques/algorithms (e.g., regression, classification, clustering) and optimization models.
• Industry Knowledge: Familiarity with supply chain processes such as demand forecasting, inventory management, procurement, logistics, and distribution.
• Analytical Thinking: Strong problem-solving skills with the ability to analyze complex data sets and translate insights into actionable recommendations.
• Personal competencies
• Ability to work independently and as part of a team in a consulting environment.
• Attention to detail, with the ability to manage large data sets and complex analysis.
• Communication: Excellent verbal and written communication skills to present findings clearly to non-technical stakeholders.