Lexica is an advanced dialogue system with machine learning components. It’s our goal to gradually replace existing application and create a more intelligent system. To pursuit this, we started R&D into Deep Learning techniques for Natural Language Understanding and Dialogue Generation. You will join an open-minded and capable team which built all technical solutions ground-up in a short period of time. We learn and create in a dynamic and fast-paced environment.
The User Experience and Interaction (UXUI) team helps everyone focus on the end user. UX Researchers create understanding and empathy around both stated and unstated user needs. In your role, you will learn how to conduct empirical research on conversational agents and work directly with the Chief UXUI to improve our product features. You are expected to have a good mathematical foundation, some knowledge about psychology, and/or basic programming capabilities using at least one data processing language. Ideally, you have some prior working or research experience with AI can perform under fast-paced and dynamic environment. On the job, you will learn the fundamentals of human-computer interaction and combine these concepts with your domain knowledge and programming skills to help improve user experience.
You'll do more than just crunch numbers though: through reports, presentations, visualizations and team engagement, you'll provide a UX perspective on quantitative data to understand users and quantify problems. You can also learn and contribute using qualitative methods (e.g., field visits, ethnography, interviews, surveys, usability testing, and logs analysis) to explore and analyze behaviors and motivations of users.
You are encouraged to identify new opportunities for user experience improvements, making the connection between our products and users intuitive and accessible. You’ll inspire change at various stages of product development by delivering compelling, written, in-person and visual presentations on your findings.
Responsibility
- Define and measure quantitative UX goals and metrics in collaboration with chief UXUI, Product Manager, and Engineers.
- Examine existing data and product designs to generate hypotheses and plans for high-impact research.
- Assist Chief UXUI to prioritize research to improve user experience.
- Develop code and statistical models to understand user experience.
- Communicate convincingly the research finding through reports, presentations and visualizations to Chief UXUI
- Assist data collection and labelling for deep learning techniques
- Assist Chief UXUI in making actionable steps for expert users and non-experienced users
Requirements
- BA/BS degree in Computer Science, Human-Computer Interaction, Cognitive Sciences, Mathematics, Statistics, Psychology, Service Design or a related field, or equivalent practical or research experience.
- Experience in a programming language commonly used for data manipulation and computational statistics (such as Python, R, Matlab, C++, Java or Go), and with basic understanding of database.
- Effective interpersonal, communication, negotiation and collaboration skills.
- Knowledgeable about statistics and/or psychology.
Additional Requirements
- 1-2 year(s) of experience in an applied research setting or experience working in a human-computer interaction environment
- Some experience conducting semi-structured interviews, contextual field visits, usability studies either live or remote.
- Some experience in survey design (i.e., Qualtrics) and experimental design
- Good understanding of the strengths and shortcomings of different research methods, including when and how to apply them during the product development process.
- Demonstrated expertise in multivariate statistics and the experimental designs;
- Proficiency in programming computational and statistical algorithms for large data sets primarily for UXUI needs;
- Excellent command of research questions within a given domain (e.g., human-agent/robot interaction, social computing, datavis, conversational agents), and of technical tools for the analysis of data within that field.