CV

Education

• Stanford University — MS, Education Data Science
  Sep 2024 – Jun 2026
  Focus: behavioral data science, machine learning, longitudinal modeling, LLM evaluation. Accel Leaders Program Fellow.
• Wellesley College — BA, Data Science
  Sep 2019 – Dec 2021

Experience

• Aura — Data Scientist
  Palo Alto, CA · Apr 2024 – Mar 2026
  • Analyzed large-scale behavioral and transactional data to identify patterns related to child online safety and financial fraud.
  • Built data pipelines for monitoring behavioral signals and supporting real-time safety alerts.
• DraftKings — Senior Data Science Engineer / Data Science Engineer
  Boston, MA · Jan 2022 – Mar 2024
  • Developed collaborative filtering and hybrid recommendation models to personalize sports content.
  • Built ML pipelines with MLflow for reproducibility and model lifecycle management; led migration of data science systems to Amazon EKS.

Research

• Stanford Autonomous Agents Lab — Graduate Researcher
  Dec 2024 – Present

  SPIRALS (LLM safety in mental-health contexts), Screenome Project, and Master's thesis. See research.

• Fulbright Canada · Mitacs Globalink — Research Intern
  Montréal, Canada · Jun 2021 – Aug 2021

  NLP analysis of 10,000+ citizen complaints (SeeClickFix, Google Maps) for sentiment and topic insights on urban infrastructure.

• Wellesley College — Senior Honors Thesis
  Feb 2021 – Nov 2021

  NLP analysis of 800+ U.S. commencement speeches (1890–2020). ASA/CAUSE Honorable Mention.

• Harvard Business School — PRIMO Fellow
  Cambridge, MA · Jun 2020 – Aug 2020

  Examined ethnic discrimination signals in Indian labor markets via web-scraped leadership data and regression analysis.

• Wellesley · Institute for Mathematics and Democracy — Student Researcher
  Jan 2020 – May 2021

  Co-authored a paper on how political conflicts and compromises can be expressed using simplicial algebraic topology.

Publications

1. Moore, J., Mock, A., Mai, Y., Anthis, J. R., Louie, R., Mehta, A., Klyman, K., Liang, P., Haber, N., Lin, E., & Ong, D. (2026). DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots. Submitted to NeurIPS 2026 Datasets and Benchmarks Track.
2. Cerit, M., Mock, A., Almanon Feliciano, V., Robinson, T. N., Reeves, B., Ram, N., & Haber, N. (2026). Within-person prediction of depressive symptom change using year-long Screenome data and CES-D assessments. arXiv preprint.
3. Zarei, F., Mahajan, A., Mock, A., & Nik-Bakht, M. (2024). Extracting Domain Folksonomy. Proceedings of the Canadian Society for Civil Engineering Annual Conference.
4. Zarei, F., Mahajan, A., Mock, A., & Nik-Bakht, M. (2023). Extracting Domain Folksonomy for the Built Environment — An Automated Approach. Canadian Society for Civil Engineering Annual Conference, 45–56.
5. Mock, A., & Volić, I. (2021). Political structures and the topology of simplicial complexes. Mathematical Social Sciences, 114, 39–57.

Teaching

• Stanford University — Course Assistant
  Jan 2025 – Mar 2025 · Sep 2025 – Mar 2026

  CS224G Building Apps with LLMs Inside and CS145 Big Data Systems.

• Inspirit AI — Head of Deep Dives & Instructor
  Jul 2021 – Dec 2025

  Lectured on AI for high schoolers; ran the advanced ML "Deep Dives" program for 100+ students.

• Wellesley College Math & CS — Teaching Assistant
  Feb 2020 – Dec 2021

  Tutored and graded for math courses ranging from calculus to complex analysis.

Service & mentorship

• Hack.Diversity — Alumni Mentor (2022–2025). 1:1 mentorship for fellows on data science careers.
• DraftKings Circles — Mentorship Program Lead, Women's BRG (2022–2024). Launched and ran a 200+ participant program.

Skills

• Languages (programming): Python, SQL, R
• Stats / analysis: statistical modeling, hypothesis testing, experimental design, A/B testing
• ML / modeling: recommendation systems, NLP, LLM evaluation, time-series, clustering
• Tools: Pandas, NumPy, scikit-learn, Databricks, MLflow, AWS, Kubernetes, Snowflake, Tableau