Data Scientist - AI
IBMRomania5 hours ago
Full-timeRemote FriendlyEngineering, Information Technology
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Introduction
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
Your Role And Responsibilities
As a Data Scientist with expertise in Artificial Intelligence, you will skillfully combine data analysis and business acumen to tackle cognitive computing challenges. You will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. Your primary responsibilities will include:
Required technical and professional expertise
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
Your Role And Responsibilities
As a Data Scientist with expertise in Artificial Intelligence, you will skillfully combine data analysis and business acumen to tackle cognitive computing challenges. You will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. Your primary responsibilities will include:
- Design AI Solutions: Architect and deliver AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models, and experience in tools like Github Copilot and Amazon Code Whisperer.
- Develop Cognitive Solutions: Create comprehensive cognitive solutions that effectively process and analyze both structured and unstructured data, utilizing expertise in NLP, ML, and other specialized areas such as Image Processing, Video Processing, Voice Processing, or Watson technologies.
- Implement AI Frameworks: Apply strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face, to develop and deploy AI models.
- Manage AI Project Lifecycle: Oversee the full AI project lifecycle, from research and prototyping to deployment in production environments, ensuring successful project delivery.
- Collaborate with Stakeholders: Work with various stakeholders to identify business problems and leverage the power of artificial intelligence for cognitive computing, driving business value through AI-driven solutions.
Required technical and professional expertise
- Programming: Proficient in Python and SQL, with experience using Git for version control. Skilled in key data science libraries such as Pandas, NumPy, Scikit-learn. Experience with Snowpark/Snowflake ML is a plus.
- Data Visualization: Experienced in creating analytical visualizations using Seaborn, Matplotlib, and similar libraries. Competent in developing interactive dashboards in Power BI.
- Cloud Technologies: Hands‑on experience with Snowflake as a cloud data platform for data engineering, analytics, and machine learning workflows.
- Machine Learning: Solid expertise in developing supervised and unsupervised learning models, from feature engineering to evaluation.
- Statistics & Experimentation: Strong grounding in statistics, probability, predictive and prescriptive analytics, and experimental design, including A/B testing.
- Data Analysis: Confident in working with large, complex datasets to extract insights and support decision‑making.
- MLOps: Practical experience scaling, deploying, and monitoring industrialized machine learning solutions in production environments.
- Industry Knowledge: Experience working within the Fast‑Moving Consumer Goods (FMCG) sector and understanding its analytical challenges.
- Collaboration: Proven ability to work effectively as part of multidisciplinary, global teams.
- Insight Translation: Skilled at distilling complex datasets into actionable, business‑oriented insights aligned with stakeholder needs.
- Communication: Able to present statistical findings and model outputs clearly and effectively to non‑technical audiences.
- Agility: Demonstrates an agile mindset and thrives in dynamic, fast-paced environments with multiple priorities and evolving requirements.
Key Skills
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