Associate Data Scientist

Introduction
As a Data Scientist at IBM you will help transform our clients’ data into tangible business value by analyzing information communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns you will work to solve real world problems for the industries transforming how we live.

Your Role and Responsibilities

At IBM we are committed to leveraging cutting-edge technology and data-driven insights to deliver exceptional solutions across our business operations. The IBM CIO plays a critical role in accelerating our business and technology platform transformation and increasing the productivity of every IBMer using AI-powered technology.

We are seeking an Associate Data Scientist to assist in the development and implementation of advanced data solutions that drive strategic initiatives. The candidate would join the analytics team in the CIO’s AI Automation and Data Platform group. The Associate Data Scientist will be responsible for leveraging IBM’s watsonx products as well as open-source solutions and latest technology to enable AI and generative AI solutions. Responsibilities will include supporting Senior Data Scientists and CIO leadership to enable data driven business outcomes and actionable insights.

The ideal candidate should be experienced in applying advanced statistical methods and machine learning to large datasets.

Key Responsibilities:

• Collaborate with business leaders engineers and analysts to define and prioritize data-related opportunities
• Work closely with data engineers to ensure data availability quality and integration for data science initiatives
• Extract compile and validate data conducting analysis using standard analytic and/or data science tools and techniques
• Work with senior data scientists and CIO leadership on analysis projects and support their data needs
• Assist in the development of automated reports and dashboards
• Build and maintain scalable data pipelines and machine learning models in production environments
• Continuously explore emerging technologies and methodologies in AI machine learning and data science to accelerate IBM CIO transformation

Required Technical and Professional Expertise

• 3+ years’ experience with a programming language and/or statistical tool (R or Python preferred)
• 3+ years’ experience with performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• 3+ years’ experience working with data visualization or dashboarding tools (Cognos Analytics or Tableau)
• Strong analytic skills related to working with structured and unstructured datasets
• 3+ years’ experience with core statistical analysis skills (e.g. linear regression logistic regression k-means clustering significance testing etc.)
• Experience supporting and working with cross-functional teams in a dynamic (e.g. Agile) environment
• 2+ years’ experience in research and/or experimental design
• Experience with generative AI techniques to develop innovative solutions for enterprise industry use cases
• Strong experience with big data framework such as Spark
• Experience with Iceberg: a high-performance format for large analytic tables
• Proven ability to translate business challenges into data science solutions
• Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders
• Strong analytical abilities and problem-solving skills and an informed evidence-based approach
• Degree in statistics mathematics physics or another quantitative field. Quantitative degrees in social sciences (political science sociology psychology etc.) are also acceptable
• Ability to manipulate process and extract value from disconnected datasets
• Curiosity for exploring complex problems through analytics and insights

Preferred Technical and Professional Expertise

• Proficiency in Machine Learning frameworks (e.g. scikit-learn TensorFlow PyTorch) LLMs (e.g. IBM Granite IBM Slate Llama) and NLP/GenAI tools (e.g. HuggingFace LangChain)
• Experience with SQL and relational databases
• Experience with cloud platforms for data science projects
• Familiarity with DevOps practices CI/CD pipelines and MLOps tools
• Previous experience in large-scale enterprise IT environments