Point72 Software Engineer interview questions

13 Software Engineers have shared notes from their Point72 interviews, with the questions they were asked in each round. That is 34% of the 38 Point72 interview notes on Screna AI.

13 Software Engineer interview notes

Point72·Software Engineer·Online Assessment (OA)

Jun 2026
Point72 data engineer assessment, two independent coding tasks sent as an OA. One SQL, one PySpark. Nothing behavioral, just code.
  • Write a SQL query that, for each candidate, shows the top three distinct vote totals by state, including state names and counts formatted into place columns (1st, 2nd, 3rd). States tied at the same vote count should be grouped together and sorted alphabetically.
  • Implement several methods of a PySpark job class: initialize a Spark session, filter transactions to only valid ones based on account existence and balance rules, count distinct source accounts, and return the top 10 source accounts by transaction count as a dictionary.

“This one took me longer than it should have.”

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Point72·Software Engineer·Online Assessment (OA)

Jun 2026
Point72 gave me a PySpark coding problem as part of their data engineering interview. It was a self-contained OA with a skeleton codebase and unit tests to pass, which I actually prefer over live coding with someone watching you.
  • Implement a PySpark job class for bank data mining. The class needs four methods: one to initialize a local SparkSession, one to join accounts and transactions filtering out rows where the transfer amount exceeds the source account balance or the destination account doesn't exist, one to return the count of distinct source account numbers, and one to return the top 10 source accounts by transaction count as a dictionary.

“The filtering logic in the second method is where I spent most of my time.”

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Point72·Software Engineer·Technical Phone Screen

Jun 2026
Got a SQL problem for a Data Engineer role at Point72. One question, but it was a proper one, not just a basic join or group by situation.
  • Given a candidates table and a results table, write a SQL query that produces a per-candidate report showing their full name and top 3 states by vote count. Each place column should display as 'State (votes)'. If multiple states tie at the same rank, list them alphabetically separated by commas in that rank's column. Ranking should be based on distinct vote totals, not row position.

“The dense rank part is what got me initially.”

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Point72·Software Engineer·Technical Phone Screen

May 2026
Point72 data engineer interview with a Python coding problem that looked like a standard stock trading puzzle but had enough moving parts to trip you up if you weren't careful. The decorator requirement was the part I didn't see coming.
  • Given an array of daily stock prices, implement a function that finds the optimal set of non-overlapping buy/sell transactions to maximize total profit, and returns each transaction as a structured tuple with buy day, sell day, prices, and profit.
  • Wrap the transaction-finding function with a decorator that validates the input prices list against a set of constraints before the function runs.
  • Implement a report generator that takes the prices array and produces a human-readable string summarizing each transaction and the total profit.

“The core algorithm isn't too bad once you realize you can just capture every upward slope.”

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Point72·Software Engineer·Technical Phone Screen

May 2026
Point72 quant engineer interview that went pretty deep into linear regression, specifically around computational approaches when your dataset is massive. Not a brutal round but there was one moment where I definitely froze up before things clicked.
  • How do you estimate the coefficients in linear regression, and what approach would you use when the number of observations is much larger than the number of features?

“Started with gradient descent which they accepted, but then they pushed for a closed-form solution.”

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Point72·Software Engineer·Take-home Assignment

May 2026
Point72 Data Engineer take-home involving two PySpark problems. The second one had five functions to implement and a few genuinely tricky spots if you're not careful about how Spark reads CSVs by default.
  • Set up a Spark session with the correct master and application name configuration.
  • Filter a medical bills table to keep only records that have a matching entry in an eligibility table.
  • Generate a full name column by combining first and last name from the eligibility table and return the result in the required schema.
  • Find the member who paid the highest amount, sorting by the payment column.
  • Calculate the total amount paid across all records and return it as an integer scalar.

“Straightforward.”

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Point72·Software Engineer·Online Assessment (OA)

May 2026
SQL-heavy online assessment for a Data Engineer role at Point72, one problem but it had enough edge cases to keep me busy for a while. The problem was framed as fraud detection on a crypto exchange and the output formatting requirements were brutal.
  • Given a transactions table on a cryptocurrency exchange, write a PostgreSQL query to detect potentially fraudulent activity: find all sender-recipient pairs with 2 or more transactions, then produce one row per sender showing their wallet address, a formatted time range from first to last transaction, and a concatenated string of transaction amounts sorted descending. For senders with 3 or fewer transactions just list them all with a sum; for more than 3, show the top 3 and collapse the rest into a '+ .. X more = Sum' suffix. Order final output by total amount descending.

“The core logic, CTEs for filtering pairs then joining back to detail rows, wasn't the hard part.”

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Point72·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round for a Data Engineer role at Point72. Just one question but it was a meaty one, the kind where you can't really bluff your way through with a vague answer.
  • Describe a situation where you had to build a solution that worked for multiple stakeholders with competing priorities. Walk through your role, the trade-offs you faced, how you made decisions, and what happened in the end.

“This is the type of question where picking the right story matters more than how you tell it.”

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Point72·Software Engineer·Onsite - System Design / Architecture

Apr 2026
System design interview at Point72 for a data engineering role. The whole thing was focused on one big open-ended design problem around pipeline orchestration, data quality, and observability. Pretty deep technically, and the streaming failure handling question at the end had some real nuance to it.
  • How would you design a production orchestration system for batch and streaming data pipelines that handles upstream and downstream dependencies?
  • What data quality checks would you build into your pipelines? Walk through how you'd implement things like threshold checks, schema validation, null checks, primary key checks, and upstream dependency checks.
  • What would a data observability framework look like in practice?
  • If 2% of records in a streaming pipeline fail validation, do you stop the entire pipeline or keep it running? How do you decide, and what do you do with the failed records?

“This is where I started rambling a bit.”

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Point72·Software Engineer·Technical Phone Screen

Apr 2026
Got a probability question for a quant role at Point72. Short and sweet on the surface, but it requires you to actually think about geometry or covariance, not just plug into a formula.
  • X and Y are independent standard normal random variables. What is P[X > 3Y]?

“My first instinct was to set up an integral and I immediately started second-guessing myself on the bounds.”

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