Data Scientist

• Adaptable and Pragmatic: You are comfortable navigating ambiguity and evolving priorities. You adapt your approach as new information emerges and focus on practical solutions that balance rigor with speed. • Adaptable and Pragmatic: • Strong Analytical Judgment: You bring a solid foundation in statistics and applied analytics, with the ability to choose appropriate methods for the problem at hand. You understand concepts such as confidence intervals, bias, and tradeoffs, and apply them thoughtfully in real-world contexts. • Strong Analytical Judgment: • Product-Oriented Data Scientist: You have experience working on analytics that directly influence product direction or business decisions. You understand how to define meaningful metrics, evaluate impact, and connect insights to outcomes. • Product-Oriented Data Scientist: • Technically Proficient: You are proficient in Python and SQL and comfortable working with modern data stacks, pipelines, and large datasets. You value clean, well-documented, reproducible work and collaborate effectively with analytics and engineering partners. • Technically Proficient: • Clear Communicator: You can explain complex analytical concepts to non-technical audiences and focus on the “so what.” You tell compelling stories with data that resonate with executives, partners, and cross-functional teams. • Clear Communicator: • Mission-Aligned: You are motivated by improving student wellbeing and care access. You care about responsible data use, ethics, and outcomes, and you bring a “Grow Our Impact” mindset to your work. • Mission-Aligned: • Professional Experience: 4+ years of experience in data science, analytics, or a related field, including delivering analytics, models, or data products used in production environments. • Domain Experience: Experience working in healthcare, education, fintech, or other regulated or data-sensitive industries. Familiarity with healthcare or education data is a strong plus and will help you ramp more quickly. • Applied Product Analytics: Demonstrated experience applying data science in a product-driven context. You have worked on initiatives that directly informed product direction or business decisions, rather than purely exploratory or academic work. • Applied Product Analytics: • Technical Proficiency: Strong proficiency in Python and SQL for data analysis. Comfortable working with large datasets, writing complex queries, and using Python-based libraries to clean, analyze, and interpret data. • Technical Proficiency: • Statistical Judgment: Solid grounding in statistical analysis and experimental thinking. You can design and evaluate analyses with appropriate rigor and clearly interpret results, balancing precision with practical decision-making. • Statistical Judgment: • Communication Skills: Proven ability to communicate insights and analytical concepts to diverse audiences. You can produce clear visualizations or presentations and explain the “so what” to inform decisions at multiple levels of the organization. • Cross-Functional Collaboration: A team-oriented mindset with experience working closely with Product, Engineering, Design, or Clinical partners to deliver shared outcomes. • Cross-Functional Collaboration: • Ownership & Accountability: High degree of self-direction and accountability. You take initiative, manage your time effectively, and can independently drive projects from problem definition through execution and follow-through. • Ownership & Accountability: • AI & LLM Experience: Experience applying natural language processing techniques or working with large language models, even in experimental or early production contexts. • Production Analytics or ML Exposure: Experience supporting analytics or machine-learning systems in production, including validation, monitoring, or iteration over time. • Production Analytics or ML Exposure: • Data Visualization & BI Tools: Familiarity with tools such as Looker, Tableau, or similar platforms for communicating trends and insights prior to full productization. • Data Visualization & BI Tools: • Advanced Education: An advanced degree in a quantitative field (e.g., Statistics, Data Science, Computer Science, Engineering) is a plus, but not required. • Advanced Education: • Impactful Opportunity: Your work will directly influence how institutions understand and support student mental health. The insights you deliver can guide real decisions that help students access care sooner and more effectively. • Impactful Opportunity: • Professional Growth: This is a high-ownership role within a strategic product area. You’ll deepen your analytical and technical skills while expanding your product thinking and business impact through close collaboration with senior leaders. • Professional Growth: • Collaborative Culture: At Mantra, we value empathy, inclusion, and intellectual curiosity. You’ll join a mission-driven team that collaborates closely and supports continuous learning. • Collaborative Culture: • Career Advancement: As Mantra continues to grow, this role offers opportunities to expand scope and influence over time. We invest in our team’s long-term success and support individuals as they take on increasing responsibility. • Career Advancement: