Infor

The Cloud Operations Machine Learning (COML) team is seeking a Data Science Team Lead to join Infor’s Cloud Operations division. The COML team is responsible for infusing AI and Machine Learning (AI/ML) methodologies into Infor’s cloud operations.  This is a player/coach position with strong emphasis on individual contribution. As the Data Science Team Lead, you will be responsible for putting models and analyses into production on the AWS cloud, overseeing junior data scientists and data engineers, leading projects and initiatives, and providing thought leadership while working on your own analyses, data science and data engineering projects. While day-to-day activities can vary widely, data science engineers are generally responsible for building ETL data pipelines, writing/debugging analytic code, monitoring and maintaining deployed projects, performing analysis on large data sets, translating business problems into mathematical models, presenting findings to varied audiences (internal and external), and taking responsibility for the analytical integrity of our solutions.

Infor’s customers depend heavily on our servers operating at peak efficiency and maximum uptime, and any disruption in service can have adverse effects on our customers. Our customers rely on our servers to perform key business operations such as paying their employees, generating essential reports, communicating with their own customers, etc. Therefore, while this is first and foremost a data science position, our goal is improved customer satisfaction and retention. The Cloud Operations division of Infor generates an enormous amount of data for monitoring server uptime and performance, and the COML team uses that data to design and implement innovative AI/ML solutions to complex problems. Our team works on problem solving from beginning to end, from understanding the business problem, prototyping modeling solutions, designing data pipelines, and implementing algorithms in production systems.

The COML team is small but growing, and we fulfill a specialized role within Infor. We have a shared goal: to apply our extensive training and passion for problem solving to solve challenging real-world problems. This is not an academic position; it is a data engineering and applied science engineering position; we want to see our algorithm designs in production. We are always learning about new applications and opportunities to apply our talents, and scientists are free to use whatever mathematical approaches make the most sense for the problem at hand.

A Day In The Life Typically Includes

• Working in AWS to implement and deploy data pipelines and data science models
• Perform code reviews
• Optimizing SQL queries for performance
• Maintain and debug data science models already in production
• Meet with stakeholders to fully understand business problems and how to solve those problems.
• Meet with members of your team to align goals and monitor progress.
• Drive cross-team coordination to ensure that roles and responsibilities are clear and project timelines are met.
• Define data requirements and perform exploratory data analysis.
• Design and test different AI/ML models and algorithms.
• Prototype and optimize different AI/ML models to identify the optimal modeling approach for any given data problem.
• Translate business problems to mathematical models and validate understanding with stakeholders.
  
  

Basic Qualifications

What You Will Need:

• Four-year degree in one of the following (or related) fields: Data Science, Mathematics, Statistics, Economics, Computer Science, Physics, Engineering, or a related quantitative field.
• Proven experience in an engineering focused data science position, or a data engineering position with a heavy analytics data science/emphasis.
• Strong, real word experience in python (other high-level languages like Java, Go, etc. acceptable)
• Basic SQL
• Able to work both independently and as part of a team.
• A desire to continue learning new technologies and techniques.
• Experience analyzing time series data.
• Experience in a leadership capacity, either formal or informal.

Required Qualifications

• Advanced proficiency in python.
• Advanced proficiency in SQL
• Demonstrated experience in engineering solutions in the cloud (ideally AWS)
• Experience with Git and Docker
• Understanding of the AWS ecosystem and how to integrate technologies together such as Athena, Lambda, S3 etc.
• Demonstrated real-world experience in designing and implementing a full data science production pipeline, from ETL, to data pre-processing, to model prototyping, to model deployment and inference.
• Ability to develop complex algorithms when necessary and simple algorithms when possible.
• Strong knowledge of mathematics/data analysis and statistics
• Familiarity with advanced AI/ML techniques such as boosted models and tree-based models etc.
• Excellent communication skills (eg. the ability to communicate effectively and efficiently with a broad range of audiences.)