Principal Data Scientist

Principal Data Scientist

Requirements

• Master’s degree or related work experience in Data Science, Mathematics, Statistics, Operations Research, Computer Science or a related field. PhD a Plus
• 10 -15 years of experience in strategic planning within Supply Chain, business analytics, or a similar role, with a strong focus on data-driven decision-making.
• Proficiency in programming languages such as Python, R, or Scala, and experience with data analysis libraries and frameworks (e.g., pandas, scikit-learn, TensorFlow, PyTorch, PuLP, SciPy, SimPy).
• Experience in advanced forecasting techniques (e.g., ARIMA, Prophet, LSTM)
• Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights and strategic recommendations.
• In-depth supply chain knowledge.
• Fluent in structured and unstructured data, its management, and modern data transformation methodologies
• Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders.
• Proven track record of leading strategic initiatives, driving organizational change, and delivering measurable business results.
• Ability to thrive in a fast-paced, dynamic environment, and manage multiple priorities effectively.
• Strong leadership and collaboration skills, with the ability to build consensus and drive alignment across diverse stakeholders.

Responsibilities

• Develop predictive models and analytical frameworks to forecast market demand, assess competitive dynamics, predict demand, optimize inventory levels, and inform strategic decision-making.
• Utilize time series analysis, machine learning, and statistical techniques to improve forecast accuracy.
• Analyze large datasets to identify trends, patterns, and opportunities for improvement in supply planning.
• Build and validate predictive models to forecast inventory needs and minimize stockouts and overstock situations.
• Continuously monitor and refine models to ensure accuracy and reliability.
• Utilize methods such as linear programming, queuing theory, and simulation to optimize inventory and production workflows.
• Develop optimization models to improve supply planning and logistics.
• Work with the supply chain team to implement inventory optimization strategies.
• Conduct scenario analysis to support decision-making processes.
• Conduct in-depth analysis of internal and external data sources to identify market trends, customer behaviors, and strategic opportunities.
• Collaborate with cross-functional teams to define strategic priorities, establish performance metrics, and track progress against strategic goals.
• Utilize deep learning models such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models for complex product classification and segmentation tasks.
• Implement prescriptive analytics techniques to recommend actionable insights for product categorization and segmentation, enabling targeted marketing and inventory management strategies.
• Lead strategic data science initiatives to support key business objectives in Inventory Optimization / Planning area.
• Mentor and coach junior team members and contribute to the development of a high-performing and collaborative data science team.

Preferred Qualifications

• Experience in strategic consulting, management consulting, or corporate strategy is a plus.