About the position
The Lead, Spend Data Analytics is responsible for implementing the design, development, deployment, and maintenance of predictive, prescriptive, and statistical models for Procurement savings and cash flow initiatives, pipeline opportunities, risk mitigation, and supplier development activities. The incumbent will bring an expertise in forecasting, optimization, data mining, analysis, and analyzing complex datasets. The Lead will conduct studies with the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms. Additional responsibilities include summarizing concise and professional reports and presentations of findings to a variety of internal clients, as well as working with other departments to achieve the overall company objectives.
Responsibilities
- Collect, consolidate, cleanse and preprocess data from various internal and external sources to ensure quality and reliability.
- Explore and visualize data to identify patterns, trends, and relationships.
- Create and execute machine learning algorithms and statistical models.
- Use programming, mathematical, statistical, and analytical skills to interpret data and format for use within Procurement.
- Provide project related scenarios with initial recommendations based on data interpretation.
- Provide tailor-made solutions based on data to help Procurement/Medline achieve unique objectives and goals.
- Prepare reports outlining business forecasts, estimates or proposals based on data analysis, as needed.
- Lead cost optimization and productivity initiatives and opportunity searches.
- Create and evaluate cost models based on financial data and industry research.
- Provide negotiation support and data insights for negotiations and RFx processes.
- Drive operational excellence for data usage, storage supporting best practices to reduce costs and improve financial performance.
- Management of data needs, and analytics for Spend Management Function.
Requirements
- Bachelor's degree in a quantitative field such as statistics, applied mathematics, financial mathematics, computer science, engineering, operations research, or a related field.
- A minimum of 5 years of experience.
- Experience in client-facing roles.
- Advanced statistical programming proficiency with R or Python.
- Experience with other programming and data manipulation languages (SQL, Hive, Spark, C/C++, Java, Ab Initio).
- Effective communication at multiple levels within and outside the organization.
- Strong analytical, critical thinking, and creative problem solving skills.
- Project and time management skills with the ability to manage multiple assignments effectively.
- Excellent communication skills with an ability to translate complex financial models into simple, understandable concepts.
- Ability to simplify strategy in executable phases.
Nice-to-haves
- Master's Degree in Data Science, Statistics, Mathematics, Computer Science, or Engineering.
- Proven ability to operate independently in a complex and dynamic, matrixed environment.
- Familiarity with operations and procurement data and solutions.
- Strong relationship building capabilities.
- Knowledge of IT Systems, AI influence in today's processes.
Benefits
- Bonus eligibility.
- Comprehensive benefits program.
