AI & Data Engineer
Role details
Job location
Tech stack
Job description
As an AI Data Engineer at Kyndryl you are the bridge between business problems and innovative solutions. Here you convert business problems to hypotheses and build, validate, and deploy models to solve them using well-defined methodologies, domain expertise, consulting, software engineering, statistics and mathematics.
You'll wear many hats, and each day will present a new puzzle to solve, a new challenge to conquer. You'll collect and explore data, seeking underlying patterns and initial insights that will guide the creation of hypotheses. Utilizing statistical and mathematical modeling techniques, you'll have the opportunity to create models that hold the key to solving intricate business challenges. With an acute eye for accuracy and generalization, you'll evaluate these models to ensure they not only solve business problems, but do so optimally.
Additionally, you're not just building and validating models - you're deploying them as code to applications and processes, while ensuring that the models you've selected maintain their business value throughout their lifecycle. Your expertise doesn't stop at data; you'll become intimately familiar with our business processes and have the ability to navigate their complexities, identifying issues and crafting solutions that drive meaningful change in these domains. You will develop and apply standards and policies that protect our organization's most valuable assets - ensuring that data is secure, private, accurate, available, and usable. Your mastery extends to data management, migration, strategy, change management, and policy and regulation.
Requirements
Do you have experience in Visual Studio?, You're good at what you do and possess the required experience to prove it. However, equally as important - you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused - someone who prioritizes customer success in their work. And finally, you're open and borderless - naturally inclusive in how you work with others., * Knowledge of modeling tools and programming languages, e.g., Azure ML, Vortex AI AutoML, SageMaker, or Python
- Excellent problem-solving, analytical, and critical thinking skills
- Communication and presentation skills, with the ability to convey complex data insights to both technical and non-technical audiences
- Ability to manage multiple projects simultaneously, while maintaining a high level of attention to detail
Preferred Skills and Experience
- Degree in a quantitative discipline, such as mathematics, statistics, computer science, or mechanical engineering
- Professional certification, e.g., Open Certified Data Scientist
- Cloud platform certification, e.g., AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, or Microsoft Certified: Azure Data Scientist Associate
- Understanding of social coding and Integrated Development Environments, e.g., GitHub and Visual Studio
- Experience in at least one domain, e.g., cybersecurity, IT service management, financial services, or health care