Research Data Scientist
- Portland, ME
- $86,490-122,164 per year
- Permanent
- Full-time
Do you want to be part of an exciting new Institute focused on the fusion of human and machine intelligence into working AI solutions? We are launching a pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. The Institute for Experiential AI (EAI) is built around the challenges and opportunities made possible by human-machine collaboration. The Institute provides a framework to design, implement, and scale AI-driven technologies in ways that make a true difference to society. Our ability to respond to the opportunities afforded to society will depend on training and building a workforce that is AI-capable and prosperous. Founded in 1898, Northeastern is a global research university and the recognized leader in experience-driven lifelong learning. Our world-renowned experiential approach empowers our students, faculty, alumni, and partners to create impact far beyond the confines of discipline, degree, and campus.The Culture:
Here at the Institute of Experiential AI (IEAI) we are committed to the highest of standards in all that we do. Working at the Institute of Experiential AI offers opportunities, an environment, a culture that just aren’t found together anywhere else. This is the right place for you if you’re curious, motivated by the future of technology and want to be part of a unique community that works on high-impact business and societal problems.This is a 1-year fixed term position.Summary:
This position supports the Institute in delivering data science and AI projects and expertise to its industry partners and researchers. Assist in delivering data science and AI courses and professional development programs to learners across the University and industry. Help build AI products that will solve the most pressing issues for organizations, including Responsible AI. Be part of a fast-growing team that will develop and maintain a cutting-edge data platform, acquire data sets for research and education purposes, and use
data science strategically to support the Institute’s mission.Qualifications:Education & Experience:
- Graduate degree (Masters/PhD) in Computer Science, Engineering, Mathematics, Statistics, or similar disciplines and two or more years of professional experience, or can convincingly demonstrate this level of skill.
- Experience assisting technical staff in the completion of projects.
- Experience communicating with technical and non-technical stakeholders and translating business
- Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
- Professional experience developing machine learning solutions and applying them in real-world scenarios.
- Proficiency with machine learning frameworks and pipelines in SKLearn, Numpy, Pandas, and PyTorch.
- Proficiency with deep learning frameworks such as PyTorch, TensorFlow, LangChain, HuggingFace,
- Professional experience developing solutions using NLP, computer vision, or forecasting.
- Proficiency with statistical computer languages such as Python or R.
- Proficiency with relational database systems (SQL) and object-based data stores.
- Ability to define and solve logical problems for technical applications.
- Knowledge of and ability to select, adapt, and effectively use various programming methods.
- Knowledge of and ability to select, adapt, and effectively use large AI foundational models.
- Experience with distributed data systems such as Apache Spark.
- Expertise in analyzing large, complex, multi-dimensional datasets with various tools.
- Expertise in hypothesis testing and AB testing.
- Proficiency in Linux and version control software (git).
- Familiarity with Object-oriented programming languages such as Python, Java, C# or C++.
- Familiarity with Agile / Scrum development practices.
- Aptitude to independently learn new technologies, prototype, and propose software design and solutions.
- Excellent verbal and written communication skills
- Drive to learn new technologies, statistical methods, and data manipulation techniques.
- Ability to communicate effectively across academia and industry.
- Team player who can collaborate effectively across many teams within the University.
- Open-minded and assertive when collaborating and working within our team and with other groups within
- Assisting technical solutioning using latest research, technical delivery of projects by defining tasks, by providing contributions (architecting, coding, scaling, and deploying), conducting experiments and synthesizing results
- Serve as a technical representative in internal and external meetings
- Support in developing technical stack (e.g., datasets, infrastructure) for execution on projects