WHAT WE DO:
Flagright arms fintechs & banks with the best-in-class technology to combat financial crime and meet AML compliance regulations. Our AI-native, no-code platform can be integrated within a week thanks to our API-first approach, which drastically undercuts the industry standard of 2-4 months. Flagright's comprehensive product suite includes real-time transaction monitoring, customer risk scoring, merchant monitoring, case management, and sanctions screening among other industry-leading features. Unique to the market, our AI Forensics module equips fincrime fighters with an immersive investigative experience that drives vigilance and operational efficiency in financial crime prevention efforts. We are a Y Combinator-backed company based in Berlin, Singapore, and Bangalore, serving customers from 6 continents.
ABOUT THE ROLE:
As a Data Science Intern at Flagright, you will be part of building the first iteration of Flagright’s AI/ML Systems. You will work on setting up the core foundation of data science operations and processes within Flagright and come up with efficient and automated data quality controls and track the causes of any possible issues through data flows.
This is a remote position, so you will need to be self-motivated and able to work independently under minimal supervision.
At Flagright, we offer exciting career growth opportunities for motivated individuals who are looking to take the next step in their careers. We have a very open and transparent culture, so you will also have the opportunity to contribute to any aspect of the business. Nothing here is beyond your reach.
If you are highly driven, enthusiastic, and looking for an exciting opportunity to join an early-stage startup, we want to hear from you.
# 🛠 You will
Research, develop, design, and build models for threat detection, guiding processes for signal ingestion, data analytics, and automation to improve detection and investigation of potentially malicious behaviors pertaining to financial transactions.
Build statistical, machine learning, and simulation models on large datasets, including unstructured data from disparate sources.
Solve real world problems pertaining to anti-fraud systems and financial crime prevention using machine learning.
Drive the creation, collection and processing of new data and the enrichment of existing data sources.
Develop technical and functional requirements to deploy novel detection and vulnerability identification capabilities that mitigate emergent and current threats.
Work closely with customers to deploy ML models, collect feedback and build a data collection and enrichment process.
# 🙌 Your profile
PHD candidate in data science, statistics, economics, engineering, finance, mathematics or a relative quantitative field at a university in the US, UK, or Europe (Required)
A proven track record of translating large and ambiguous business problems in mathematical models and developing data scientific solutions
Good understanding of databases, data structures and testing methodologies
Experience in Python programming, including libraries like Pandas, Numpy, sklearn, OR-tools
Excellent communication skills in English, both written and verbal
Analytical mindset, strong problem-solving and communication skills paired with reliability
# 💯 Preferred Qualifications
Experience working on data cleaning and data preparation
Strong preference for backgrounds in the financial sector
Strong knowledge of undergraduate statistics: distributions, uncertainty, biases, hypothesis testing, etc
2+ years of experience as a Data Scientist or similar position
Knowledge and/or experience (professional or non-professional) in LLMs
# 🤗 Benefits
Work alongside a highly competent, top-tier team (Y Combinator, ex Palantir, AWS, Revolut, Zalando).
Great career development opportunities in a fast-growing company.
Low bureaucracy, minimal meetings, async communications culture, international culture, flat organization.
Great career development opportunities in a fast-growing early-stage startup.
Do something meaningful; help stop human trafficking, money laundering, and child labor; Be a part of enabling the future of how money moves.
Fast-moving, challenging and unique business problems.
If you would like to be a part of enabling the future of fintech startups, please apply!
About the Interview Process:
R1: Exploratory chat with talent lead (30 minutes). This step is to get to know you better and help you learn more about us. We’ll talk about your background and prior projects/experiences, what drives and motivates you, and what you seek in your next role.
R2: Take-home task: It's an important step in our process. We will give you a problem statement related to role to have a deeper understanding of your approach and technical skills and to give you an idea of what we actually do.
R3: Technical Discussion with our founder and CTO (1 hour) with Madhu. We will dive into technical abilities, product thinking and overall fit. For the “fit” portion, we are again looking for ownership and autonomy, but we also dig deeper into past projects and experience. This is evaluated throughout the process -- in how you communicate your approach, solutions and overall thinking.
R4: Behavioral + Cultural Alignment with the founding team (1 hour) with Harish. We’re going to be looking for specific examples of times in your past roles when you have demonstrated high ownership skills and an execution-minded attitude that is critical to success as part of our team.
Commoditize AML compliance & fincrime prevention so that startups can focus on their core business to innovate and compete globally
4 jobsSubscribe to Rise newsletter