Chief Analytics Office (CAO) - Data Scientist

Technical Execution and Leadership: 

• Develop and deploy AI models and data analytics solutions.
• Support the implementation and optimization of AI-driven strategies per business stakeholder requirements.
• Help refine data-driven methodologies for transformation projects

Data Science and AI: 

• Design and implement machine learning solutions and statistical models, from problem formulation through deployment, to analyze complex datasets and generate actionable insights.
• Learn and utilize cloud platforms to ensure the scalability of AI solutions.
• Leverage reusable assets and apply IBM standards for data science and development.

 Project Support: 

• Lead and contribute to various stages of AI and data science projects, from data exploration to model development.
• Monitor project timelines and help resolve technical challenges.
• Design and implement measurement frameworks to benchmark AI solutions, quantifying business impact through KPIs.

Strategy & Collaboration: 

• Ensure alignment to stakeholders' strategic direction and tactical needs.
• Work with data engineers, software developers, and other team members to integrate AI solutions into existing systems.
• Contribute technical expertise to cross-functional teams.
• Required education
• Bachelor's Degree
• Preferred education
• Master's Degree
• Required technical and professional expertise
•  Education: Bachelor's or Master's in Computer Science, Data Science, Statistics, or a related field is required; an advanced degree strongly preferred.

Experience: 

• 2-4 yearsof experience in data science, AI, or analytics with a focus on implementing data-driven solutions.
• Experience with data cleaning, data analysis, A/B testing, and data visualization.
• Experience with AI technologies through coursework or projects.

Technical

Skills:

• Proficiency in SQL and Python for performing data analysis and developing machine learning models.
• Knowledge of common machine learning algorithms and frameworkslinear regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM), neural networks, and deep learning frameworks such as TensorFlow and PyTorch.
• Experience with cloud-based platforms and data processing frameworks.
• Understanding of large language models (LLMs).
• Familiarity with IBM's watsonx product suite.
• Familiarity with object-oriented programming.

 Analytical

Skills:

• Strong problem-solving abilities and eagerness to learn.
• Ability to work with datasets and derive insights.

Strategic, Communication, and Project

Skills:

• Strategic thinking and business acumen.
• Strong problem-solving abilities.
• Good communication skills, with the ability to explain technical concepts clearly.
• Enthusiasm for learning and applying new technologies.
• Strong project management skills, with the ability to balance multiple initiatives, prioritize tasks effectively, and meet deadlines in a fast-paced environment.