Associate Data Scientist

Who You Are

You are a quantitative thinker who wants to develop further as both a data scientist and an engineer. You are skilled at finding the precise mathematical kernels of real-world problems and want to bring that talent to bear on the business questions facing the world’s leading financial services companies. You are excited to apply your existing expertise in fields such as statistics and computer science to solve mission critical problems.

You are excited to work at a fast-paced startup where you will have a chance to expand your scientific and engineering skills to new areas. You share Quantifind’s commitment to winning together, and are eager to see your coworkers build on the technical foundations you will be creating. You are passionate about maintaining the high scientific and engineering standards required to enable your peers.

Above all, you are a curious and independent problem solver who is motivated to find a place where your skills can have real impact.

Quantifind helps some of the world’s biggest banks catch money laundering and fraud. Quantifind also works with government agencies to use the same platform to uncover criminal networks and combat money laundering committed by internationally sanctioned entities. Unlike other players in this space, Quantifind delivers results as Software-as-a-Service (SaaS) with consumer-grade user experiences.

Quantifind is a data science technology company whose AI platform uncovers signals of risk across disparate and unstructured text sources. In financial crimes risk management, Quantifind’s solution uniquely combines internal financial institution data with public domain data to assess risk in the context of Know Your Customer (KYC), Customer Due Diligence (CDD), Fraud Risk Management, and Anti-Money Laundering (AML) processes. Today these compliance processes are burdened by ever-increasing regulatory responsibilities and an expectation of frictionless transactions.

Legacy technologies demand increasingly more human resources as the operations expand;
Quantifind’s solution offers a way to cut through the inefficiency and enhance effectiveness through Machine Learning driven solutions that resolve for both accuracy and relevance.

To help you succeed, we provide a supportive environment that fosters collaboration between teams and team members, where learning and professional growth are considered a key part of your success, and of ours. We offer a flexible work environment with a family friendly work-life balance.

Members of the Data Science team carry solutions all the way through initial scoping of the problem, performing exploratory analysis, model training, and finally putting highly performant implementations into production. As a team member your duties will include:

• Collaborating with fellow team members and key stakeholders, such as, Product Managers, Platform Engineers to explore ideas, test hypotheses, and prototype solutions.
• Working in an agile environment breaking down complex problems into smaller manageable tasks with the help of your teammates and manager.
• Leveraging SQL, Python and PySpark to analyze large unstructured data sets to answer key business questions, inform next steps or set up modeling tasks.
• Writing complex pipeline code often involving NLP enrichment steps to process large data sets.
• Training machine learning models to solve complex problems.
• Product ionizing models in a Scala codebase following software engineering best practices.
• Validating models using standard and custom performance metrics.
• Leveraging Large Language Models (LLMs) to scale up various data science tasks (for example: data labeling, extracting structured information, …)
• Participating in code reviews.

• MS or higher in the following areas:
  Statistics, Mathematics, or Computer Science
• At least 1 year of professional industry experience, in addition to your academic experience
• Outstanding analytical skills and the ability to communicate quantitative results to technical and non-technical audiences
• Strong knowledge of Statistics/Probability/Machine Learning including core concepts of…