Data Scientist - Decisions

Data Scientist - Decisions


As a Data Scientist, you will partner closely with a cross-disciplinary group of staff, including a mix of engineering, product, data, coaching, and clinical staff, to collect, analyze, and share evidence that will inform critical business operations decisions and organizational storytelling. In particular, you’ll work on 6 high-level stages that will help move your stakeholder groups toward evidence-informed actions: data collection, availability, methodology of analysis, access, analysis, and interpretation. Through this work, you’ll help to create a culture of evidence-based decision-making that will increase our organization’s impact on our mission of supporting people in crisis.


  • In partnership with stakeholders, identify and implement new metrics and improve old metrics to reveal or monitor organizational challenges or opportunities;

  •  Develop and maintain dashboards and other visualizations that track performance metrics and show where we can improve our service;

  • Use a mix of research methods, including regression analysis, survey design, qualitative research, literature reviews, and A/B testing to generate evidence and insights;

  • Be a strategic partner and work with stakeholders to connect analysis to key decisions that affect the organization. Our team’s output is analysis, but our outcome is impact;

  • Evaluate new products and programs alongside stakeholders (eg, a new volunteer communication strategy);

  • Clarify what conclusions the team can draw from what may be imperfect data, and maximize team learnings;

  • Provide peer-reviews that ensure we are producing valid, reliable, and interpretable analyses;

  • Consider ethics, equity, security, privacy, and confidentiality, in all work;

  • Spread knowledge, provide mentorship, and promote research best practices;

  • Learn from your colleagues, stretch yourself, and grow as a scientist and teammate;

  • Manage your time successfully by focusing on priorities, and delivering on deadlines.


  •  2+ years of relevant experience

  • Proficiency in SQL and experience with at least one of the following statistical tools:

    Python, R, SPSS, STATA, or SAS

  • Experience using mixed research methodologies, including two or more of the following:

    survey design, qualitative research, A/B testing, statistical methods, machine learning.

  • Experience building charts in visualization tools like Sisense, Looker, and/or Tableau.

  • Understanding of essential scientific and research principles and how to apply them, e.g.,

    the scientific method and hypothesis testing, forms of research bias, experimental design, types of variables, privacy and confidentiality, ethical research.

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