Associate Data Scientist 2026

IntroductionIn this role, you will join IBM Consulting via our world-class Associates Program for university hires. As an Associate Data Scientist at IBM Consulting, you will have the opportunity to work with a diverse range of clients worldwide. Our clients' technical and business needs are constantly evolving. We're hiring inspired, talented individuals who believe no problem is too big to solve.We focus on your professional development through ongoing learning, mentorship, development of technical skills, and continuous personal growth, all grounded in a culture of coaching and career advancement. If you see yourself as someone who never stops learning and who wants to unleash your potential, the IBM Consulting Associates Program is for you.A career in IBM Consulting is rooted in long-term relationships and close collaboration with clients across the globe.You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat.Curiosity and a constant quest for knowledge serve as the foundation for success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions that result in ground-breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.Your Role And ResponsibilitiesAs an Associate Data Scientist at IBM, you will work to solve business problems using leading-edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for:Implementing and validating predictive and prescriptive models, creating and maintaining statistical models with a focus on big data and incorporating machine learning techniques in your projectsWriting programs to cleanse and integrate data in an efficient and reusable mannerWorking in an Agile, collaborative environment, partnering with other data scientists, engineers, consultants, and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviorsCommunicating with internal and external clients to understand and define business needs and appropriate modeling techniques to provide analytical solutions.Evaluating modeling results and communicating the results to technical and non-technical audiences.These positions are anticipated to start in 2026. We have positions open in these locations:Atlanta, GAAustin, TXChicago, ILHouston, TXNew York, NYPreferred EducationBachelor's DegreeRequired Technical And Professional ExpertiseStrong fundamentals in Mathematics and Computer Science (algorithms)You're proficient in least one of the statistical programming languages, such as R, Python, Scala, SAS, SPSS, or MatlabYou have a basic understanding of or experience with predictive/prescriptive modeling skillsYou have strong technical and analytical abilities, a knack for driving impact and growth, and some experience with programming/scripting in a language such as Java or PythonYou're great at solving problems by looking at things differently, debugging, troubleshooting, and designing and implementing solutions to complex technical issuesWillingness to travel up to 100%Preferred Technical And Professional ExperienceYou thrive on teamwork and have excellent verbal and written communication skills.You have a basic understanding of Cloud (AWS, Azure, etc.)Familiarity with constructing usable data sets from multiple structured and unstructured data sources