Field Data Scientist Internship, DataVisor
Customer Success Team
Paid on hourly rate $20-25/hour
Office located in Mountain View, CA
ML-powered fraud detection
Be an early applicant
ML-powered fraud detection
101-200 employees
Be an early applicant
Paid on hourly rate $20-25/hour
Office located in Mountain View, CA
101-200 employees
Company mission
To deliver the world’s most sophisticated AI-powered solutions to keep companies and their customers safe from fraud and abuse.
Role
Who you are
- If you have a passion for big data mining, real-world problem research and solving, and data-driven solution building, we’d love to hear from you!
- U.S. Citizen (required)
- Currently pursuing, or recently obtained a BS/MS in Data Science, Statistics, Machine Learning, or a related field
- Proficiency in at least one object-oriented programming language (e.g., Python, Java, C++)
- Proficiency in using SQL queries to conduct data joining and pattern analytics
- Strong foundation in data structures and algorithms; ability to write efficient, optimized code
- Strong analytical, problem-solving, and critical thinking skills
- Excellent project management and communication abilities
- Familiarity with big data technologies (e.g., Hadoop, MapReduce, Spark) is a plus
What the job involves
- As a Field Data Scientist Intern on the Customer Success team, you will work directly with real-world industry data, understand the data structure and data schema, research the customer’s specific business problems, analyze the patterns within the datasets that could be utilized to describe and capture the fraud attacks, and come up with effective detection strategies
- You’ll collaborate with our Technical Account Managers (TAMs), Solution Data Scientists, and the fraud teams on the customer side, to develop, test, and implement new strategies or adjustments for existing rules, in our Risk Decision Engine
- You will use manual review feedback and labels to evaluate the effectiveness of the strategies, and build dashboards to track the overall trends and detection performance metrics
- Research and understand real-world fraud problems e.g. Scam and Check Fraud
- Understand and document the data structure, data flow and data schema of the relevant data needed to solve the problems
- Analyze large-scale datasets to identify fraud attack patterns and attack evolutions
- Research and understand the tools and data signals needed to help solve the problems, e.g. Unsupervised model score, Supervised model score, 3rd party data signals
- Conduct feature engineering and strategy building to capture the patterns identified
- Test the features and strategies created and quantitatively evaluate their performance
- Present the results to TAMs and the customers, and gather feedback
- Conduct strategy tuning and iterations based on the feedback gathered
- Implement the finalized strategies to production, and build dashboards to track and monitor performance
Our take
As the use of online shopping and banking continues to rise, so too does the opportunity for fraud, with criminals exploiting the gaps in defences that come with an increasingly novel digital environment. DataVisor provides the leading fraud detection solution that leverages machine learning to identify threats, to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.
Traditional fraud solutions have not been designed to handle digital data, and they are especially ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify the patterns which allude to fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen. Another problem with some systems has been that, in the name of security, they might delay ultimately good customers from accessing services. With DataVisor this becomes a non-issue, as the pattern of a non-malicious user can also be identified with speed.
DataVisor has seen considerable investment - that will fuel its continued expansion across the globe - and has an impressive list of customers. The company has also made several partnerships that will act towards strengthening its product offering. For example, it is extending its analytics and fraud detection through partnership with Equifax, by gaining access to its rich consumer identity data.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Dec 2022
$40m
LATE VC
Feb 2018
$40m
SERIES C
Total funding: $94.5m
Company benefits
- Stock Options
- Commuter Passes
- Paid Time Off
- Catered Lunch and Dinner
- Team and Company Outings
Company values
- Take a results-driven approach.
- Prioritise team spirit and hard work.
- Be honest, curious, and maintain the highest levels of integrity.
Company HQ
Mountain View, CA
Articles
Leadership
Yinglian Xie
(CEO)Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.
Fang Yu
(CPO)Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.
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