Introduction
We are seeking a skilled Data Scientist to join our internal Cloud Economics team. In this role, you will apply advanced statistical techniques, machine learning, and predictive modeling to analyze cloud costs, optimize resource allocation, and identify cost-saving opportunities.
A career in IBM Software means you'll be part of a team that transforms our customer's 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
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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 modeling.
- 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
- Bachelor's degree in Data Science, Computer Science, Statistics, or a related field
- 3+ years of experience in data science, preferably in cloud computing (AWS, Azure, or Google Cloud, IBM Cloud) or IT infrastructure
- Strong programming skills in Python, R, or similar languages and proficiency in SQL and experience working with large datasets
- Expertise in machine learning techniques and statistical analysis and experience with big data technologies (e.g., Hadoop, Spark)
- Strong problem-solving skills and ability to translate complex data into actionable insights
- Self starter who can engage with stakeholders across the company to help drive cross-organisational improvements
Preferred Technical and Professional Expertise
- Master's degree or PhD in Data Science, Computer Science, Statistics, or a related field
- Experience with cloud cost management and optimization tools
- Knowledge of FinOps practices and cloud economics principles
- Familiarity with time series analysis and forecasting techniques
- Experience with data visualization and reporting tools (e.g., Tableau, Power BI, IBM Cognos, Apptio)
- Understanding of IT infrastructure and resource management concepts