Data Analyst

Data Analyst Location: Remote or New York City Type: Summer Internship (with possible extension to full-time) Compensation: $40 to $60 per hour Company: Blank Slate About the job Blank Slate is building the next generation of systems to help teams move faster, think better, and operate at scale. We create intuitive, high-impact products, leveraging data science, cognitive science, and a strong user interface, that solve real problems for modern organizations. Our team values ownership, curiosity, and speed - bringing together engineers, data scientists, and builders who are excited to tackle complex challenges and turn ideas into reality. Opportunity We are looking for a Data Analyst Intern to join our Data Science team for a high-impact summer internship. In this role, your primary mission will be to analyze Blank Slate’s dataset from every angle, identifying trends, behavioral patterns, knowledge gaps, product opportunities, and business insights that help us understand how people learn, retain, forget, and improve over time. This role will report directly to our senior data scientist and work closely with our CEO. You will be expected to think creatively, ask good questions, dig deeply into the data, and translate your findings into clear insights that can inform product development, customer strategy, dashboard design, and company decision-making. This is a strong fit for someone who enjoys open-ended analytical work and wants to work on real-world product data. Key Responsibilities Dataset Exploration & Analysis: Analyze large-scale user learning data to uncover trends, anomalies, behavioral patterns, and performance insights. Data Cleaning & Manipulation: Clean, structure, transform, and prepare datasets for analysis using Python, SQL, pandas, NumPy, and related tools. Trend & Pattern Discovery: Identify usage patterns across users, teams, organizations, cards, decks, time periods, and learning outcomes. Learning & Retention Analysis: Explore relationships between engagement, repetition, accuracy, time spent, forgetting, and knowledge improvement. Data Mining: Search for hidden signals in the dataset that could inform product features, manager dashboards, customer insights, or internal strategy. Visualization & Communication: Build clear charts, tables, and written summaries using tools such as matplotlib, notebooks, and spreadsheets. Collaboration: Work closely with the CEO and senior data scientist to turn raw data into practical recommendations for the business. Insight Generation: Develop hypotheses, test them against the data, and explain what the results suggest in plain language. Required Qualifications Education: Current junior, senior, or master’s student majoring in Statistics, Data Science, Mathematics, Computer Science, Finance, Economics, or a related quantitative field. Programming & Analysis: Strong working knowledge of Python and SQL. Python Libraries: Experience with NumPy, pandas, and matplotlib. Data Skills: Solid understanding of statistics, data analysis, data mining, data acquisition, data manipulation, and data cleaning. Version Control: Familiarity with Git. Analytical Thinking: Ability to work through ambiguous questions, identify useful patterns, and separate real signal from noise. Communication: Ability to explain findings clearly to both technical and non-technical teammates. Nice to Have Basic understanding of machine learning concepts. Experience with Google Cloud Platform. Experience with Docker. Experience analyzing product usage data, learning data, behavioral data, or large operational datasets. Interest in cognitive science, spaced repetition, education technology, human performance, aviation, defense, or operational readiness. What We Offer Competitive Compensation: $40 to $60 per hour. Compensation is hourly for the summer internship role. High-Impact Work: Your analysis will not sit on a shelf. The insights you generate will directly inform product decisions, customer dashboards, data science priorities, and business strategy. Executive Exposure: You will work directly with our CEO and our senior data scientist, giving you close exposure to company-level decision-making. Real Data, Real Problems: You will work with a large real-world dataset generated by actual users in operational environments. Analytical Ownership: You will have room to explore the dataset deeply, propose your own questions, and surface insights the team may not have thought to look for.