Data Scientist

Introduction
A career in IBM Software means you’ll be part of a team that transforms our customers challenges into solutions.
Seeking new possibilities and always staying curious we are a team dedicated to creating the world’s leading AI-powered cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers so the door is always open for those who want to grow their career.
IBM’s product and technology landscape includes Research Software and Infrastructure. Entering this domain positions you at the heart of IBM where growth and innovation thrive

Your Role and Responsibilities
The Data Scientist role requires a highly analytical individual proficient in Python programming database management and data science methodologies. You’ll focus on extracting insights from data developing and implementing machine learning models managing big data infrastructure and supporting AI-driven product development.
Key Responsibilities:

• Data Collection and Cleansing: Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making.
• Data Exploration and Visualization: Explore and visualize data using advanced techniques to uncover insights and trends.
• Statistical Analysis: Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modelling.
• Machine Learning and Deep Learning: Develop and implement machine learning and deep learning models to address business challenges.
• ML-Ops / AI-Ops: Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management.
• Big Data Management: Manage big data infrastructure and execute data engineering tasks for efficient data processing.
• Version Control and Collaboration: Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration.
• AI-Driven Product Development: Design create and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives.

Required Technical and Professional Expertise

• Industry Experience: Minimum 8+ years of experience in the IT industry. 2 years of experience in developing AI/ML solutions in Python
• Technical Proficiency: Proficient in Python programming Java Go Node.js JavaScript TypeScript React. Coding for Data Science: Ensures robust & reproducible implementation of algorithms and experiments. Deep experience with python libraries.
• Database Management: Strong understanding of database concepts and experience working with Postgres relational database OpenSearch documentation database.
• Data Science Skills: Strong background in data science statistics mathematics and analytical techniques.
• Machine Learning Expertise: Expertise in machine learning and deep learning methodologies including foundation models. Statistics Machine Learning and AI: Builds expertise in tools & techniques to evaluate trust and transparency. Masters use of data science platforms and tools
• Big Data Technologies: Familiarity with big data technologies and data engineering practices.
• Version Control Systems: Experience with version control systems particularly Git and proficiency with GitHub for code collaboration.

Preferred Technical and Professional Expertise

• Experience with DevOps and Cloud computing – Docker Kuberenetes Openshift
• Agile Application Development & Scrum methodologies.
• Familiarity with z/OS and mainframe technologies.
• Experience with Continuous Integration / Continuous Delivery (CI/CD) methodologies
• Familiar with cloud-based platforms and services