As a Data Scientist at IBM, you will help transform our clients'
data into tangible business value by analyzing information,
communicating outcomes and collaborating on product development.
Work with Best in Class open source and visual tools, along with
the most flexible and scalable deployment options. Whether it's
investigating patient trends or weather patterns, you will work to
solve real world problems for the industries transforming how we
Your Role and Responsibilities
AI and Automation (AIOps) is a game-changer for IT
Companies that embrace data for insights and automation of IT
Operations will lead and those who do not will fall behind.
We are building an elite team of data science practitioners and
DevSecOps / SRE experts to help IBM's clients simplify and automate
IT Operations driven by data and AI. This elite team will include
data engineers, machine learning engineers, operations engineers,
and data journalists.
The team will engage directly in solving real-world IT Operation
problems and be responsible for delivering the First-Of-its-Kind
AIOps solution for IBM clients around the globe. The elite team
will work with client teams to engineer AIOps in their environment,
refining AI models; ultimately helping clients to gain deeper,
AI-driven insights from their data and enabling them to prevent and
fix IT issues at scale. This will enable client IT teams to focus
on strategic projects, with AI as the enabler for this new Digital
As a member of the team, you should be deeply familiar with the
challenges that IT leaders face and be equipped to make
recommendations for where and how to apply AI in the IT context.
You should have in-depth knowledge of systems, solutions, and
hybrid cloud environments that is used in IT Operations to identify
the right set of data to train AI models. An understanding of SRE's
role and responsibilities and operation metrics would be a plus.
You are proficient and knowledgeable with container orchestration
platforms such as IBM Kubernetes Services and Red Hat OpenShift.
Understanding of and hands-on experience with pods, containers,
deployments, services, and other essential components of the
Kubernetes platform is a must-have. Experience using monitoring
tools such as Grafana and Sysdig and log aggregator tools such as
LogDNA and Humio is also desired. You should also have excellent
debugging skills to help identify and fix, for instance, deployment
issues of containerized applications. You enjoy implementing
utility scripts in BASH and Python to automate repeatable tasks
that are commonly associated with ETL processes. You should be
familiar with the process of cleaning, formatting, and organizing
large data collections in order to create quality data sets that
can be used for model training, You are also familiar with Docker
technology principles and the required steps for containerizing
applications. In this team, you will jump-start the process of
using AI to transform client IT systems and guide them through
their adoption of AI for IT Operations.
- Help clients appreciate the power value of AIOps to transform
their IT Operations and progress them from a lead to a win for
- Work with each client to identify high-value use cases for AI
in IT with highest business impact.
- Break that use case(s) down into discrete MVPs (minimal viable
- Collect, prepare, and augment large data sets to train
- Work with new datasets, client systems, and tools.
- Build and validate new models.
- Deploy, monitor and retrain models.
- Scope Application definition
- Automate repeated IT tasks, driven through insights from the AI
- Work with the client team to measure the impact of AIOps
against defined metrics.
- Communicate effectively with line-of-business end-users to
discover pain points and use cases, lead project definitions, and
convey the business value of the project.
- Guide and mentor clients to become self-sufficient AIOps
- Work with IBM Internal teams to document and provide feedback
to productize repeatable use cases.
While working across all these industries, you will also get to
travel the World as these engagements will require that the team
spend several weeks at client sites working on IT Ops problems with
a diverse team.
As a member of the team you will have a T-shaped skill set,
having a broad knowledge base, but also in-depth expertise in key
Required Technical and Professional Expertise
- At least 4 years experience - Data Engineering/ Data Modeling/
- At least 4 years experience - IT Operations, System and
Application management and monitoring.
- At least 4 years experience - Computer Science, Programming
skills, including containerization.
Preferred Technical and Professional Expertise
- 2+ years experience as an IT Sys admin or SRE
- 4+ years experience -Machine Learning pipeline - data
ingestion, predicting, explaining, deploying and diagnosing over
- 5+ years experience - Business and Leadership
- Some Management experience is preferred