Staff Machine Learning Research Scientist

Why you should join our team: 

• Our work is transforming the way people in pain access support at their fingertips
• Our work is innovative in the crisis response space
• Our dynamic, fun, and diverse culture
• Our meaningful cause, led by empathy and innovation
• Our strong values at the center of all we do
• Our commitment to diversity, equity and inclusion
• Our commitment to engagement and belonging
• Our commitment to our employees and their holistic wellbeing
• Our  value of work/life balance
• Our growth mindset and prioritize professional development
• Our leaders who truly care

What you'll be doing:

The purpose of the Research & Impact department is to demonstrate and amplify Crisis Text Line’s impact for texters, our volunteer community, and broader society towards our mission of promoting well-being for people wherever they are. It is imperative that we demonstrate impact against our mission, and we consider it our duty to contribute solutions-oriented insights to the field of mental health together with an international network of affiliated partners committed to collective social impact in the context of the global mental health epidemic. The Research & Impact team serves the organization’s mission by championing the generation of compelling, evidence-grounded, data-driven content, resources, and tools for internal stakeholders and the broader mental health field. We achieve this by using AI/ machine learning and natural language processing to analyze our de-identified dataset of over 10 million conversations with texters in the United States; continuously assessing the impact of our efforts on texters, volunteers, and society; and combining our insights with publicly available data sources, to inform policy, practice, and systems change to reduce mental health inequities and improve wellbeing.

As a Staff Machine Learning Research Scientist within the Research & Impact team, you will lead foundational ML/AI efforts to deliver a consistent flow of high-quality, insightful research aimed at evidencing and optimizing impact of Crisis Text Line’s service and improving practice, policy and the broader field of mental health support in the US and globally. You will use Natural Language Processing techniques and Machine Learning models to monitor emerging trends and identify novel signals in crisis conversations so that we can generate near-real-time insights with a potential to improve the lives of people in crisis. As part of a small but nimble team working in collaboration with divisions across the organization, you will research a corpus of over 300 million text

messages related to mental health crises to pursue impactful research questions, build ML models to identify new themes, research related volunteer impacts both on and off the platform, deliver compelling data visualization and actionable insights to amplify Crisis Text Line’s impact for texters, volunteers, and society across languages, cultures, and contexts.

Reporting to the Senior Principal Research Scientist as an individual contributor, you will work in close collaboration with all members of the Research & Impact team, as well as with global network affiliates and cross-functional partners in data analytics, clinical, volunteer experience, user research, engineering, and product teams. Promoting equity, diversity, and inclusion, as well as deliberately highlighting various identities, particularly those of historically minoritized groups, is an explicit focus of our work.

Responsibilities:

Crisis Text Line is a fast moving, growing organization with a big vision and a critical mission. To serve our mission and vision, each role must be agile and flexible to meet the needs of the business, aligning their work with priorities as defined by their manager and team leaders.

Lead Machine Learning to Deliver New Research Insights for Crisis Text Line

• ML/AI/NLP engineering and model development: lead the design and implementation of  custom ML/deep learning/NLP pipelines to analyze conversational data. Pipelines will include data ingestion, preprocessing, feature generation, model selection and development, and fine-tuning. Using Python with frameworks like scikit-learn, spaCy, NLTK, Hugging Face, TensorFlow, PyTorch, Transformers, Spark, and/or similar tools, use traditional ML and Large Language Model (LLM)/transformer architectures and related strategies to analyze large datasets. This work will support research projects on mental health crises; briefs related to mental health, coping, and volunteering; and mental health and support disparities in the United States and globally.
• ML/AI/NLP model evaluation: contribute to the design and implementation of pipelines to evaluate model performance, accuracy, and reliability; and to evaluate and mitigate bias. 
• Fully own model pipelines, from data collection and labeling to deployment.
• Perform statistical analyses (e.g. hypothesis testing, linear regression, logistic regression, linear mixed effect models) in R or Python to contribute to the team’s scientific output.
• Use Spark and/or SQL to clean and transform data, join tables, and create automated ETL jobs to regularly update datasets, ensuring availability for analysis and reporting.
• Support or lead collaborative strategic research sprints, adhering to rigorous, industry-standard research methods and documentation practices, and ensuring research reproducibility.
• Visualize data (matplotlib, ggplot, plotly) to support internal and external communication of research findings.
• Write research grants, briefs, memos, technical reports, and scientific manuscripts for peer-reviewed publications. 

Communicate Results & Support Data Storytelling

• Communicate and share model performance and impact in a digestible way with the rest of the team and organization.
• Support efforts to communicate results for both technical and non-technical audiences, including ongoing management of organization-wide internal data insights and research requests as a member of the core workflow team.

Lead ML/AI Documentation and Coding Practices on the Research and Impact Team

• Implement industry standard documentation and coding protocols and practiceson the Research and Impact team.
• Provide technical assistance, code reviews, and mentorship to other members of the Research & Impact team related to ML/AI/NLP model development and implementation.
• Support the development or review of external-facing content referencing Crisis Text Line data and insights, as appropriate.

Qualifications:

• 6+ years of combined training and experience in computational social science, natural language processing, computer science, or related disciplines
• Theoretical and practical understanding of ML/AI/NLP models both for structured and unstructured data
• Experience in programming languages used for data manipulation, computational statistics, distributed computing, and ML workflows (such as Python, Spark, R, MATLAB, C++, Java, Go), and with SQL.
• Ability to write clean and modular code, maintained with version control tools.
• Extensive hands-on experience with multiple NLP techniques (task specific fine-tuning of large language models, text parsing, lemmatization, topic modeling, named entity recognition, text classification, relation extraction, sentiment analysis, etc.)
• Skills in translating research results into non-technical insights for broad consumption

Reliable High-Speed Internet Required: Must have a stable high-speed internet connection to support seamless remote collaboration, virtual meetings, online job tasks, etc.

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