Data Scientist, Robinhood
Anti-Fraud
$157-185k
Office located in Menlo Park, CA
Commission-free stock trading platform
Open for applications
Commission-free stock trading platform
1001+ employees
Open for applications
$157-185k
Office located in Menlo Park, CA
1001+ employees
Company mission
To democratize finance for all.
Role
Who you are
- The business is seeking curious, growth-minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future
- If you’re invigorated by our mission, values, and drive to change the world — we’d love to have you apply
- We are looking for a Machine Learning Engineer to help detect and reduce risk to Robinhood - a crucial role to our business and customers
- The ideal candidate is passionate about understanding the different fraud vectors at a fast-growing company and building solutions to mitigate these risks
- Familiarity with fraud domains and banking processes, including account takeover, ACH fraud, debit/credit card fraud, first-party fraud, and synthetic identity fraud
- Demonstrated expertise in building and deploying fraud models using large datasets, with a strong track record of success in fraud detection and prevention
- Knowledge of model risk governance and experience collaborating with model validation teams to ensure compliance with regulatory requirements
- Graduate degree in a quantitative field such as mathematics, economics, statistics, engineering or natural sciences (or equivalent research experience)
- Solid understanding of unsupervised learning, statistical analysis and machine learning algorithms for imbalanced datasets
- Excellent programming skills, including familiarity with either Python (numpy, scipy, pandas) or R programming languages
- Experience with Tableau, Looker, and/or Mode
- Experience communicating data driven insights
- 2 + years professional experience as a Machine Learning Engineer
- 1 year of experience working in a research setting in academic or commercial setting
- Passion for working and learning in a fast-growing company
- Strong customer empathy
- Intense sense of curiosity
What the job involves
- Insights from data power most decisions at Robinhood and our company trajectory is defined by the systems, tools, and analytics powered by this exceptional team
- As a Machine Learning Engineer working on Fraud and Risk, you would work with backend engineers, product managers and operations teams across the company to understand and mitigate the risks to our business
- Robinhood faces unique data challenges with a focus on integrating complex data streams such as rapidly changing market data, user data based on app activity, and brokerage operations data to understand user behaviour and the risks to our business
- This team is part of the larger Data Team here at Robinhood
- Combining knowledge of several research domains to improve our understanding of different risks to Robinhood and help power decisions
- Designing new machine learning systems to power the fraud prevention and risk reduction efforts at Robinhood especially in product areas
- Build production grade models on large-scale datasets to measure effectiveness across products by leveraging statistical modeling, machine learning and data mining techniques
- Collaborate with the rest of the data team and partner marketing, product, content, design teams to build data solutions and products to drive user and revenue growth
- Work with cross-functional teams to implement insights and analytical solutions to empower data-driven decision making
- Problem solving skills and a can-do attitude to dive deep into data to solve business problems
Our take
For years, traditional brokers ruled the share trading realm, charging hefty fees that locked out everyday investors. Robinhood emerged as a disruptor, offering commission-free trading and opening the door to a new generation. Its innovative model thrives on premium features like increased buying power and extended trading hours, attracting a younger audience drawn to meme stocks like AMC and GameStop.
But Robinhood's not just about quick thrills. The company claims its mission lies in catering to "the unmet needs of the next generation," evidenced by its "Robinhood Retirement" launch, targeting gig-economy workers often excluded from financial planning. This commitment to accessibility aligns with its core values.
However, 2023 brought unexpected turbulence, as Robinhood became entangled in the FTX cryptocurrency exchange bankruptcy scandal when it emerged that the US Department of Justice seized hundreds of millions of dollars of the company's shares tied to FTX founder Bankman-Fried. Despite these challenges, Robinhood successfully bought back the missing stock, and its impact on democratizing finance remains undeniable.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Some candidates hear
back within 2 weeks
39% female employees
-23% employee growth in 12 months
Company
Funding (last 2 of 13 rounds)
Feb 2021
$2.4bn
CONVERTIBLE
Jan 2021
$1bn
LATE VC
Total funding: $5.6bn
Company benefits
- Well-being - Premium medical, dental, and vision insurance
- Family & home life - Parental leave, personal prosperity benefits
- Comfort & care - Annual lifestyle stipend
- Office life - Catered meals and fully stocked kitchen, commuter benefits
- Growth - Education and training, community events, career mentorships
Company values
- Safety First: Robinhood is a safety-first company
- Participation is Power: At Robinhood, the rich don’t get a better deal
- Radical Customer Focus: We exist to make our customers happy
- First-Principles Thinking: We make bold bets and challenge the status quo
Company HQ
Downtown Menlo Park, Menlo Park, CA
Articles
Leadership
Vlad Tenev
(Co-Founder)Studied Mathematics at Stanford University, where they met their fellow co-founder. Dropped out of a PhD to start Robinhood.
Baiju B.
(Co-Founder)Studied Mathematics and Physics at Stanford University, where they met their fellow co-founder.
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