Company Overview :

IBM is a global technology leader, providing a wide range of services and solutions, including cloud computing, artificial intelligence, consulting, and infrastructure. Operating across diverse industries, from finance and healthcare to retail and manufacturing, IBM helps clients worldwide transform their businesses through innovative technology and expertise.

Role Overview :

As a Data Scientist at IBM, you will be at the forefront of developing and deploying cutting-edge AI solutions. You will collaborate with cross-functional teams, including engineers, product managers, and business stakeholders, to translate complex business problems into actionable data-driven insights. Your work will directly impact IBM's clients by enabling them to make smarter decisions, optimize operations, and gain a competitive edge through the power of data and AI.

Key Responsibilities :

- Develop and implement machine learning models, including LLMs and deep learning algorithms, to address specific business challenges for IBM's clients.

- Conduct in-depth data analysis and feature engineering to extract meaningful insights and improve model performance.

- Design and execute experiments to validate model accuracy and identify areas for improvement.

- Communicate findings and recommendations to technical and non-technical audiences through clear and concise presentations and reports.

- Collaborate with engineering teams to deploy and scale machine learning models into production environments.

- Stay up-to-date with the latest advancements in data science, machine learning, and AI, and apply them to solve real-world problems.

- Contribute to the development of innovative data science solutions and intellectual property for IBM.

Required Skillset :

- Demonstrated ability to develop and deploy machine learning models using Python and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).

- Proven experience in natural language processing (NLP) and large language models (LLMs).

- Strong understanding of statistical modeling, data mining, and data visualization techniques.

- Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.

- Ability to translate complex technical concepts into clear and concise explanations for non-technical audiences.

- A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.

- Adaptability to work in a dynamic environment and manage multiple projects simultaneously.