Ingram Micro touches 80% of the technology you use every day with our focus on Technology Solutions, Cloud, and Commerce and Lifecycle Solutions. With +$50 billion in revenue, we have become the world’s largest technology distributor with operations in 56 countries and more than 30,000 associates. We continue to strategically expand global reach with 32 acquisitions since 2012.
The ideal candidate will complement the global team by bringing a versatile empirical skill set, using modern innovative tactics and strategies to support our data analytic offerings. The Analyst will focus on executing and delivering data driven products to address project and campaign specific requirements. This includes gathering and scoping requests; working with complex data sets; executing SQL queries and building Stored Procedures; data science production automation; analysis of output and statistical models; and effectively communicating findings to stakeholders. She/He will maintain a broad understanding of the marketplace, Ingram Micro’s business model, and become educated on particular vendors, customers, or internal division’s business models and needs. Excellent SQL skills are required.
Analysis and Reporting (60%)
Requirements Gathering and Model Building: Understand client’s objectives and translate business needs into the appropriate technical models. Develop and Estimate Models: Collect, transform, and clean data from multiple sources this is why we are getting DI candidates, right?; build/maintain relational databases; develop appropriate statistical and econometric models; estimate models; perform statistical tests; interpret and review output; ensure results and models accurately address question of interest and capture real-world market dynamics.
- Support Vector Machines
- Multiple Nominal Logistic Regressions, linear regressions
- Features extraction, attributes selection
- Clustering, decision and model trees
- Numerical optimization (linear and nonlinear) with constraints
- Experimental Design
- Multiple Dimensional Scaling
- Neural Network
- Conjoint/Discrete Choice
- Price optimization, price elasticity/demand modeling
- Text mining on structured and unstructured data, sentiment analysis
Effectively listen, communicate, recommend, and present data analytic solutions to internal and external clients. Includes over the phone, video conference, and in person presentations. The team is diverse, highly collaborative, with a global presence. The associate must be willing to work overlap shifts with US time zones (PST) for effective interfacing with other managers and Subject Matter Experts (SMEs) abroad.
Program Organization and Execution (20%)
The Analyst will focus on executing and delivering data driven products to address project and campaign specific requirements. This includes gathering and scoping requests; working with complex data sets; executing SQL queries and building Stored Procedures in collaboration with Consultants and Project Managers in order to deliver excellence in Program Execution.
Job Qualifications and Educational Requirement
- Master’s degree in quantitative discipline (Statistics, Applied Mathematics, Operations Research, Computer Science, or Econometrics) and 3 years functional experience with at least 1 year applied experience within the discipline.
- She/He needs to have experience in analysis of large data sets, identifying trends and patterns, and effectively communicating both internally and externally
- Ability to independently scope data needs, tools, and analytics to solve defined business questions, and make recommendations collaboratively with senior business leaders using output from empirical analysis.
- Experience with Query Languages, Automation and Modeling Techniques (SQL, Python, R)
- Managed at least one project in which a relational database was built and utilized for analysis.
- Comfortable manipulating, transforming, and analyzing complex, high-volume, high-dimensionality data from varying sources.
- Ability to troubleshoot and identify data issues working independently and as a team.
- Experience with
- Modeling Techniques (linear regression, logistic regression, decision tree)
- Query Languages (SQL, Python)
- Automation (SQL Stored Procedures, SSIS, APIs)
- Reporting (Excel, .Net, PowerBI QlikSense)