Data Science Consultant/Manager
First seen by Alion on Sep 5, 2026.
Overview :
Consultant / Manager - Sourcing and Procurement Analytics will be responsible for leading data-driven initiatives to optimize procurement and supply chain operations. This role requires a strong understanding of statistical methods, analytical techniques, and data science applications to drive meaningful insights. The manager will take a lead on client engagement on their projects, provide technical guidance, and lead a team of analysts to solve complex procurement and supply chain challenges using advanced analytics.
Roles and Responsibilities :
- An expert in sourcing and procurement operations domain and Data Science skills.
- Responsible to solution architect, design, build, deploy, deliver, and monitor advanced analytics models for sourcing and procurement analytics.
- Interface with clients to understand business problems and translate it into analytics problems that shall deliver insights for action and operational improvements.
- Implement advanced analytics to perform spend analytics, category analytics, contract analytics, supplier management analytics, price forecasting, supply risk analytics, etc.
- Take initiatives and collaborate with different Company Internal teams and support driving sales.
- Provide innovation and thought leadership support to build key capability areas such as tools & technology, new solutions in supply chain planning and assets & accelerators development.
- Utilize statistical models, machine learning, simulation and optimization techniques to enhance procurement and supply chain operations.
- Implement analytics to evaluate supplier performance, optimize procurement costs, and mitigate supply chain risks.
Team Leadership & Development :
- Mentor and guide a team of analysts and consultants in developing analytical solutions.
- Foster a culture of innovation and continuous learning within the team.
- Ensure knowledge sharing and best practices are followed across projects.
Technology and Process Optimization :
- Drive digital transformation in procurement using AI, machine learning, and cloud-based analytics solutions.
- Leverage SQL and advanced analytics tools for data preparation, manipulation, and descriptive analysis.
- Collaborate with IT and procurement teams to improve data integration and system automation.
Experience and Education :
- A Minimum 4 - 14 years of experience in industrial/consulting or related areas is needed with at least 3 - 8 years of supply chain advanced analytics solutions design and delivery experience.
- Good to have global client experiences. Experience specifically in sourcing and procurement domain is preferred.
- Master's degree in Technology, Engineering, or a quantitative field (e.g., MSc in Statistics and Operations Research, M. Tech in Industrial Engineering, Applied Mathematics/Statistics, Computer Science).
- Certifications in one or more areas will be an added advantage : Python, AI/ML, Simulation, Optimization, any of the Cloud platforms (Azure, GCP, AWS).
Mandatory Skills :
- Proven ability to drive analytics-driven procurement transformation projects.
- Deep understanding of advanced analytics solutions - descriptive, diagnostic, predictive, prescriptive, and generative and hands-on experience in building models using machine learning, deep learning, Gen AI models.
- Experience with cloud-based solutions (Azure, GCP, AWS) for procurement analytics.
- Hands-on programming experience with any of the analytics tools, databases and visualization tools and platforms (Python, PySpark, SQL, Bigdata tools, PowerBI/ Tableau).
- Excellent written and verbal communication skills, with the ability to interact with senior stakeholders.
Good to Have :
- Proficiency in data visualization tools like Tableau/Power BI.
- Experience with procurement tools such as Ariba, Coupa, Zycus, or Ivalua.
- Prior experience in client-facing roles and managing large-scale procurement analytics initiatives.
Skills
Data Science, Data Scientist, Solution Architect, SQL, Artificial Intelligence, Python, Machine Learning, AWS, Predictive Modeling