Cyndx is an Artificial Intelligence and Natural Language Processing (NLP) platform that offers “search and discovery” solutions for entrepreneurs, start-ups, investors, and acquirers. Our subscription-based solution helps enhance capital raising, acquisitions, and other business opportunities. Our platform hosts data on over 16.5 million companies world-wide and is used by some of the largest financial institutions in the world.

We are looking for a Senior Data Scientist to work on leveraging text and financial data to build machine learning models that encapsulate the ecosystem of a banker’s lifecycle. As a part of Cyndx's Data team, you will report to the AI Engineering Manager. We are looking for individuals who thrive in fast-paced environments, are creative problem solvers and get their kicks from implementing solutions for non-trivial machine learning problems designed for the financial world and working with a team who raises the bar.

In this role, you will be working with a team of AI engineers and data scientists and are responsible for the design and development of proprietary AI algorithms, including but not limited to financial data point estimations, target recommendations, and trend predictions that would make Cyndx unique in the Fintech market space.

Note: This role is a hybrid remote role and requires candidates to work on-site Tuesdays, Wednesdays and Thursdays.

Learn More About Us

• Forbes: Couples's Complementary Skills build Successful Investment Discovery Platform
• Business Insider: How Investors are Getting Data on the Private Markets
• Benzinga: How AI and NLP are Changing the Way we Invest in Private Markets
• Cube.js: How Cyndx enhanced its financial platform with Cube.js
• Middle Market Growth: The Future of AI-Driven Deal Origination

Required

• Ph.D./M.S. in a quantitative field (Computer Science, Data Science, Artificial Intelligence, Mathematics, Economics, Statistics, etc.)
• 3 years of experience working in a data science role with at least 1.5 years in banking or in a financial setting.
• Expertise in Python and SQL
• Expertise with ML libraries like Numpy/Pandas/Scikit-learn
• Proven experience of working with financial datasets.
• deep understanding of machine learning algorithms including but not limited to regression models, classification models, clustering, boosting, and neural networks.
• Strong research mind to be able to read and understand the latest research in AI and finance.
• A creative mindset to not just solve problems, but to come up with ideas that would further enhance our products

Nice to haves

• Practical experience working with text data (web scraped text, news data, etc.)
• Practical experience working with alternative data (website traffic data, transactional data, etc.)
• Knowledge about AI pipeline tools (Kubeflow, Amazon Sagemaker, etc.)

Benefits

• Competitive pay
• Plenty of time off
• Health, dental and vision insurance
• 401k
• Catered lunch twice a week
• Centrally located offices in both NYC (near Grand Central) and West Palm Beach