IT Data Scientist - Level 2

Requisition Number: 222599 

Job Description

Cintas is currently looking for an IT Data Scientist – Level 2 to work on small to large, complex projects that requires increased skills in multiple technical environments and knowledge of a specific business area; working closely with Business Analysts, Software Engineers, and team members to understand the business requirements that drive the analysis and design of quality technical solutions that are aligned with business and IT strategies, and are in compliance with the organization’s architectural standards; responsible to work on data science, machine learning, analytics and also involved in major support issues.

 

Responsibilities:

• Engage with Business Analysts and Functional Analysts in understanding Machine Learning (ML) and Artificial Intelligence (AI) use cases and collect detailed requirements.
• Design, develop and test AI neutral network models using Tensorflow, PyTorch, HuggingFace, Keras, Scikit-learn and any Python based libraries like Panda, Numpy, Scipy, etc.
• Review data acquisition strategies and develop programs to acquire data into Data Lake / Data Warehouse from transactional SAP ERP systems like ECC, CRM, EWM, EM, BW, Hybris using various tools like HANA SDI & SDA adaptors; SLT, file, OData and other 3rd party adaptors as applicable.
• Examine the quality, trends and patterns in data using statistical algorithms provided in HANA PAL Library, traditional SQL commands and open-source libraries in Python.
• Develop machine learning models using SAP HANA Predictive Analytics Library (PAL), APL, AFL libraries in HANA XSA.
• Develop machine learning models using opensource libraries in Python and R in Vertex AI in GCP.
• Work with business applications of Artificial Intelligence using Python, Keras, ANN, CNN, RNN
• Design and develop database artifacts like Tables, Calculation Views, SQL Script Procedures to stage large amounts of input & output ML data in Data Lake.
• Design and develop analytical reports using visualization tools like SAP Analytics Cloud (SAC) and Looker to present data visually to end users.
• Participate in Software Development Life Cycle (SDLC) tasks like design reviews & approvals, detailed functional & technical documentation, migration of artifacts to production.
• Provide hyper-care during initial weeks after go-live and resolve production issues, bugs, and any disruptions.

Skills/Qualifications

Required:

 

• Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, or related quantitative field
• Minimum 3 years of analytics, data science, related IT experience, including:
  • 3 years of experience where proficiency with programming in R or Python was demonstrated
  • 3 years of in-depth hands-on relational database and reporting experience including the ability to write SQL
  • 2 years of experience working with large databases to perform complex analysis
  • 2 years of experience working in statistics and multivariate analytical techniques including multivariate regression, logistic regression, cluster analysis, design of experiments, machine learning, and decision trees
  • Experience with Google Cloud Platform – Big Query, Vertex AI

OR

• Master’s degree in Statistics, Mathematics, Data Science, Engineering, or related quantitative field
• Minimum 1 year of analytics, data science, related IT experience, including:
  • 1 year of experience where proficiency with programming in R or Python was demonstrated
  • 1 year of in-depth hands-on relational database and reporting experience including the ability to write SQL
  • 1 year of experience working with large databases to perform complex analysis.
  • 1 year of experience working in statistics and multivariate analytical techniques including multivariate regression, logistic regression, cluster analysis, design of experiments, machine learning, and decision trees.
  • Some experience with Google Cloud Platform – Big Query, Vertex AI

 

Preferred:

 

• Some experience with commercial analytic techniques including pricing, customer lifetime value, and churn modeling preferred

 

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Benefits