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1
Describe the setup and assumptions of using linear discriminant analysis (LDA).
Machine Learning
Robinhood
null
no
no
0
Describe your experience with data compliance regulations (e.g., GDPR, CCPA) and their impact on data engineering practices.
Data Engineer
Robinhood
null
no
yes
0
Describe your experience with ETL (Extract, Transform, Load) tools and frameworks.
Data Engineer
Robinhood
null
no
yes
0
Describe your experience with relational databases like MySQL or PostgreSQL.
Data Engineer
Robinhood
null
no
yes
0
Discuss your knowledge of distributed computing frameworks like Apache Spark or Hadoop.
Data Engineer
Robinhood
null
no
no
0
Discuss your knowledge of serverless computing and its benefits for data engineering tasks.
Data Engineer
Robinhood
null
no
no
0
Do you perform data wrangling and data cleaning before applying machine learning algorithms to your data analysis?
Data Science
Robinhood
null
no
no
0
Explain a tax basis and its importance in tax season.
Data Science
Robinhood
null
no
no
0
Explain the concept of partitioning and bucketing in distributed systems.
Data Engineer
Robinhood
null
no
no
0
Explain the importance of data governance and data privacy in a data engineering context.
Data Engineer
Robinhood
null
no
no
0
Explain the process of building a data pipeline from data ingestion to transformation and loading.
Data Engineer
Robinhood
null
no
no
0
Explain what Information Gain and Entropy are in a Decision Tree?
Machine Learning
Robinhood
null
no
no
0
Explain your experience with cloud platforms like AWS, GCP, or Azure.
Data Engineer
Robinhood
null
no
yes
0
Formulate the background behind an SVM and show the optimization problem it aims to solve.
Machine Learning
Robinhood
null
no
no
0
Given an array of numbers represents heights of 2-d mountains, compute the amount water stored after the rainfall among those mountains.
Data Science
Robinhood
null
no
no
0
Given an array of numbers that represent the heights of 2-D Mountains, compute the amount of water stored after the rainfall among those mountains.
Data Science
Robinhood
null
no
no
0
Have you worked with probability in a professional setting?
Data Science
Robinhood
null
no
no
0
How are decision trees trained?
Machine Learning
Robinhood
null
no
no
0
How can MLE be used to estimate values in linear regression?
Machine Learning
Robinhood
null
no
no
0
How can we describe the model setup formulaically and evaluate the posterior probabilities and log likelihood for a Gaussian Mixture Model (GMM) for anomaly detection?
Machine Learning
Robinhood
null
no
no
0
How can we determine if a new transaction should be deemed fraudulent for a Gaussian Mixture Model (GMM) for anomaly detection?
Machine Learning
Robinhood
null
no
no
0
How can we predict if a person is churning?
Data Science
Robinhood
null
no
no
0
How can you compute the overall capital gain/loss in a set of transactions?
Data Science
Robinhood
null
no
no
0
How comfortable are you with statistics and using them in your work?
Data Science
Robinhood
null
no
no
0
How could you figure out how spending on a billboard was working with multiple other variables at play?
Data Science
Robinhood
null
no
no
0
How could you figure out that spending on a billboard was working with multiple other variables at play.
Data Science
Robinhood
null
no
no
0
How did you approach defining metrics in the case study?
Data Science
Robinhood
null
no
no
0
How do we measure the launch of Robinhoods fractional shares program?
Data Engineer
Robinhood
null
no
no
0
How do we measure the launch of Robinhoods fractional shares program?
Data Science
Robinhood
null
no
no
0
How do you address multicollinearity in regression models?
Data Science
Robinhood
null
no
no
0
How do you approach cleaning and preprocessing large datasets?
Data Analytics
Robinhood
null
no
no
0
How do you approach data visualization and what tools do you prefer?
Data Analytics
Robinhood
null
no
no
0
How do you compute the new objective function?
Machine Learning
Robinhood
null
no
no
0
How do you deal with an unbalanced binary classification when analyzing a data set?
Data Science
Robinhood
null
no
no
0
How do you define good investors?
Data Science
Robinhood
null
no
no
1
How do you define good investors? How do you identify them?
Data Science
Robinhood
null
no
no
1
How do you ensure that your data analysis is aligned with business goals and objectives?
Data Analytics
Robinhood
null
no
no
0
How do you handle missing or incomplete data in your analyses?
Data Analytics
Robinhood
null
no
no
0
How do you identify them?
Data Science
Robinhood
null
no
no
0
How do you interpret the coefficients of a logistic regression model?
Data Science
Robinhood
null
no
no
0
How do you prioritize and manage multiple data analysis projects simultaneously?
Data Analytics
Robinhood
null
no
no
0
How do you stay current with the latest trends and advancements in data analysis?
Data Analytics
Robinhood
null
no
no
0
How does a random forest reduce overfitting and correlation between trees?
Machine Learning
Robinhood
null
no
no
0
How does K-means clustering work?
Machine Learning
Robinhood
null
no
no
0
How does the bias-variance tradeoff in machine learning work, and have you ever seen this tradeoff become evident in the outcomes of a model?
Machine Learning
Robinhood
null
no
no
0
How is PCA implemented?
Machine Learning
Robinhood
null
no
no
0
How well do you know Robinhood?
Data Science
Robinhood
null
no
no
0
How would the ROC curve change? If it doesnt change, what kinds of functions would change the curve?
Machine Learning
Robinhood
null
no
no
0
How would you AB test our program of giving out free stocks to new signups?
Data Science
Robinhood
null
no
no
1
How would you AB test the program of giving out free stocks to new signups?
Data Science
Robinhood
null
no
no
1
How would you address covariate imbalance in a dataset?
Data Science
Robinhood
null
no
no
0
How would you approach measuring the success of X new feature
Data Science
Robinhood
null
no
no
1
How would you build a fraud detection model with a text messaging service for transaction approval?
Data Engineer
Robinhood
null
no
no
0
How would you build a model to calculate a customers propensity to buy a particular item? What are some pros and cons of your approach?
Machine Learning
Robinhood
null
no
no
0
How would you calculate seat availability in a theater using two tables?
Data Science
Robinhood
null
no
no
0
How would you define and identify a good investor on a platform like Robinhood?
Data Science
Robinhood
null
no
no
0
How would you design a data warehouse schema for efficient querying and analysis purposes?
Data Engineer
Robinhood
null
no
no
0
How would you design a machine learning system to identify good investors on Robinhood?
Data Engineer
Robinhood
null
no
no
0
How would you design a scalable and cost-effective architecture for processing and storing large volumes of data in the cloud?
Data Engineer
Robinhood
null
no
no
0
How would you design a schema for a specific business use case, considering factors like data volume, query performance, and data relationships?
Data Engineer
Robinhood
null
no
no
0
How would you determine if spending on a billboard was effective amidst other marketing variables?
Data Science
Robinhood
null
no
no
0
How would you ensure data security during data ingestion, storage, and processing?
Data Engineer
Robinhood
null
no
no
0
How would you fix the model in case of a data quality issue where decimal points were removed from some values?
Data Science
Robinhood
null
no
no
0
How would you handle data quality issues and ensure data integrity in a pipeline?
Data Engineer
Robinhood
null
no
no
0
How would you identify synonyms?
Machine Learning
Robinhood
null
no
no
0
How would you improve the app's Watchlist?
Data Science
Robinhood
null
no
no
0
How would you optimize and tune a Spark job for performance?
Data Engineer
Robinhood
null
no
no
0
If you receive an offer from Robinhood, how long do you think you'll stay here?
Data Science
Robinhood
null
no
no
0
In a machine learning problem, if you have a high-dimensional dataset, how would you go about handling it?
Machine Learning
Robinhood
null
no
no
0
In order to improve user retention and lower churn, the growth team at Robinhood is interested in understanding why and which users withdraw money from their Robinhood account. A user is considered churned when their equity value (amount of money in Robinhood account) falls below $10 for a period of 28 consecutive cale...
Data Science
Robinhood
null
no
no
0
In what ways do batch normalisation and instance normalisation differ?
Data Science
Robinhood
null
no
no
0
In which real-world scenarios do overfitting and underfitting tend to occur? How do these occurrences affect the accuracy and performance of the model?
Machine Learning
Robinhood
null
no
no
0
Is a logistic model still valid if a key variable has data quality issues?
Data Engineer
Robinhood
null
no
no
0
Is your classifier able to discriminate between fraud and not-fraud effectively?
Machine Learning
Robinhood
null
no
no
0
Predict user churning based on user balance account and trading activity
Data Science
Robinhood
null
no
no
0
Say we are running a probabilistic linear regression which does a good job modeling the underlying relationship between some y and x. Now assume all inputs have some noise added, which is independent of the training data. What happens?
Machine Learning
Robinhood
null
no
no
0
Show mathematically that the decision boundaries are linear for linear discriminant analysis (LDA).
Machine Learning
Robinhood
null
no
no
0
Show that in the setup of a linear regression model where the error terms are normally distributed, maximizing the likelihood of the data is equivalent to minimizing the sum of squared residuals.
Machine Learning
Robinhood
null
no
no
0
sql coding exercise: calculating seat availability on plane given two tables SEATS and PLANE.
Data Science
Robinhood
null
no
no
0
Tax Basis It's tax season! Given a set of transactions, find out the cost basis for each sell and compute the overall capital gain/loss.
Data Science
Robinhood
null
no
no
0
Tell me about a time when you were given the freedom to explore a business problem with very few parameters. What was your initial approach to attacking this project?
Data Science
Robinhood
null
no
yes
0
what are false negatives
Machine Learning
Robinhood
null
no
no
0
What are some cost functions you might consider for a linear regression model when some sensors are prone to complete failure?
Machine Learning
Robinhood
null
no
no
0
What are some of the differences between a histogram and a box plot?
Data Science
Robinhood
null
no
no
0
What are some ways you might improve your model or what other models might you look into?
Machine Learning
Robinhood
null
no
no
0
What are the differences between OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) databases?
Data Engineer
Robinhood
null
no
no
0
What are the different types of data models (e.g., relational, dimensional, NoSQL) and when would you use each?
Data Engineer
Robinhood
null
no
no
0
What are the optimization strategies you're versed in, and can you summarize their operation?
Machine Learning
Robinhood
null
no
no
0
What are the three components of error in modeling?
Machine Learning
Robinhood
null
no
no
0
what are the trade-offs between them in terms of dollars and how should the model be weighted accordingly?
Machine Learning
Robinhood
null
no
no
0
What are the two properties of ideal clustering?
Machine Learning
Robinhood
null
no
no
0
What are the two types of models for classification?
Machine Learning
Robinhood
null
no
no
0
What criteria would you use to determine whether Robinhood should roll out push notifications for market openings to all users?
Data Engineer
Robinhood
null
no
no
1
can you provide a dynamic range in the data source for a pivot table?
Data Analytics
Salesforce
null
no
no
0
create a view in tableau to analyze the sales, profit, and quantity sold across different subcategories of items present under each category.
Data Analytics
Salesforce
null
no
no
0
describe a situation where you had to go above and beyond to get the data you needed to make a decision.
Data Analytics
Salesforce
null
no
yes
1
describe a time when you had to explain your findings in a way that was both simple and accurate.
Data Analytics
Salesforce
null
no
yes
0
describe a time when you had to explain your findings in terms that were both simple and accurate.
Data Analytics
Salesforce
null
no
yes
0
describe a time when you had to explain your findings to someone who was not familiar with data analysis.
Data Analytics
Salesforce
null
no
yes
0
describe a time when you had to present your findings in a way that was both convincing and compelling.
Data Analytics
Salesforce
null
no
yes
1