IBM Data Scientist 

India, Karnataka, Bengaluru 

440356571

• 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