Job Description

Introduction
At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Your Role and Responsibilities
We are seeking a Staff Research Scientist with a demonstrated publication track record and skills in computational statistics and machine learning, with familiarity with geospatial data and/or capability to model large scale longitudinal environmental and biomedical data.

Strong communication skills and ability to work independently and collaboratively are highly desired traits. We are seeking a leader who is motivated by addressing complex data analysis problems, including learning from less and heterogeneous spatial and temporal data. We want someone who is interested in interdisciplinary & transdisciplinary collaboration with the scholarly community, business units within IBM, and with external partners and clients. In this unique role, you will interact with the brightest minds in AI and will help bring AI research ideas into scalable, robust systems. Your can-do approach to creative problem solving will be critical to the success of our teams and the company.

Your Responsibilities

• Support and collaborate with other research scientists, engineers, interns and partners in internal IBM Research and partnership projects, helping to design and undertake statistical and machine learning research and implementation on various data modalities.
• Plan and manage own research contributions, organise, and delegate work to other members of the team and coach other members of the team on specialist methods and processes.
• Provide leadership by having influence in the translation of the global research strategy into meaningful strategic objectives for the local research lab.
• Contribute to research funding and commercial proposals and develop relationships with collaborators on Data Science, AI, and related topics.
• Remain current on new AI/Data Science methods and trends.
• Regularly write good quality research articles for peer-reviewed journals, book chapters, and reviews. Present papers at top tier AI/ML/Statistics/Data Science conferences and participate in seminars to disseminate research. Produce patents.
• Be willing to assist with the supervision of interns, junior members of the team and students hosted for vacation programming.
• Perform any other duties as may reasonably be required to ensure the efficient running of the collaborative projects and programs at the lab.
• Maintain confidentiality regarding research data, business strategy and activities when interacting with non-collaborating researchers.

Required Technical and Professional Expertise

• A Doctoral degree computer science/ engineering, electronic engineering, applied mathematics, statistics or data science and related technical fields with some depth in applied mathematics, statistics and machine learning.
• Experience with analysis of multiple modes of data and from different sources. Competence in modelling spatial, time series (or sequential data more generally) will be required for this role.
• Experience with model building and algorithm development, familiarity with Bayesian methods will be advantageous.
• Experience with machine/deep learning frameworks, such as Scikit-Learn, PyTorch, TensorFlow, Keras, etc.
• Familiarity with open-source programming software such as Python & R and coding tools/environments such as GitHub, Jupyter Lab
• Parallel computing experience will be beneficial
• Required to have demonstrable scientific publication record (peer-reviewed scientific journal & conference papers), including first author publications
• Experience in conducting and supervising applied research in AI/ML or data science as well as the development of research projects
• Strong communication and organization skills are required
• Embodiment of growth mindset (Collaborative and committed to continuous career development and learning)

Preferred Technical and Professional Expertise
n/a

IBM