Lead, Spend Data Analytics

Summary

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.

Duties and Responsibilities

Duties and 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.
• Data Interpretation: Use programming, mathematical, statistical, and analytical skills, to interpret data and format for use within Procurement.
• Insight Extraction and Recommendations: Based on interpretation, be able to provide project related scenarios with initial recommendations.
• May be asked to provide tailor-made solutions, based on data to help Procurement/Medline achieve unique objectives and goals.
• Reporting and Proposals: Prepare reports outlining business forecasts, estimates or proposals based on data analysis, as needed.
• Lead cost optimization and productivity initiatives and opportunity searches. This involves analyzing spending data, commodity supply trends, and market intelligence to identify cost-saving measures.
• Create and evaluate cost models based on financial data and industry research. This includes extracting key information essential for management decision-making and external benchmarking.
• Provide negotiation support and data insights for negotiations and RFx (Request for Proposal/Quote) processes to support Sourcing and Procurement teams.
• 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

Salaries vary by location and are based on numerous factors, including, but not limited to, the relevant market, skills, experience, and education of the selected candidate. If an estimated salary range for this role is available, it will be provided in our Target Salary Range section. Our compensation package also includes bonus eligibility and a comprehensive benefits program. Benefits information can be found at Sidley.com/Benefits.

Target Salary Range

$146,000 - $160,000 if located in Illinois

Qualifications

To perform this job successfully, an individual must be able to perform each Essential Duty and Responsibility (the “Essential Duties”) satisfactorily.  The requirements listed below are representative of the minimum knowledge, skill, and/or ability required.  Reasonable accommodations may be made to enable individuals with disabilities to perform the Essential Duties.  If you need such an accommodation, please email staffrecruiting@sidley.com (current employees should contact Human Resources).

 

Education and/or Experience: 

Required:

• 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, with evidence of initiative-taking
• 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 – translating strategy to execution is critical

Preferred:

• 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 op