Offer summary

Qualifications:

MSc or Ph.D. in Computer Science, Statistics, Physics, Mathematics, or Econometrics., At least 4-5 years of experience as a data scientist, with expertise in Time Series Analysis., Background in the financial industry, including risk and credit assessments., Proficiency in Python and statistical analysis, with strong analytical skills..

Key responsibilities:

Research state-of-the-art generative AI and classical machine learning models.

Define data collection plans and requirements.

Build models from proof of concept to production-ready solutions.

Collaborate with ML engineering team for deployment and performance monitoring.

Job description

Description

Liquidity is the largest tech-enhanced financial asset management firm in the world. With $2.5B AUM across funds focused on North America, Asia-Pacific, Europe, and the Middle East. Liquidity operates globally with offices in Tel-Aviv, Abu Dhabi, New York, London and Singapore.

The firm’s patented machine learning and decision science technology enables it to deploy more capital through more deals faster than any firm in capital markets history, establishing it as the fastest-growing provider of non-dilutive and equity financing to mid-market and late-stage companies. Liquidity is backed by leading global financial institutions including Japan’s largest bank, MUFG, Spark Capital, and KeyBank Asset Management.

Liquidity offers a dynamic and fast-paced work environment. With an open-door policy and a commitment to high standards, the company is growing rapidly and seeks team members who aspire to grow alongside it.

About the role:

We are looking for an outstanding Senior Data Scientist to join the team and revolutionize how investment is done. You’ll be harnessing the power of machine learning models and advanced mathematical techniques to develop the first-ever real-time, no-code corporate credit score platform.

If you are a bright, out-of-the-box thinker, and love coming up with solutions for real-life big-data problems, and have expertise in Large Language Models and Time Series Analysis, we are looking for you!

Responsibilities:

Research of state of the art generative AI models as well as classical machine learning models.
Define data collection plan and requirements
Build models from POC to production-ready
Work closely with ML engineering team driving production release and performance monitoring
Provide guidance to the product team and user community to increase product effectiveness

Qualifications:

MSc/Ph.D. in Computer Science, Statistics, Physics, Mathematics, Econometrics, or equivalent
Minimum 4-5 years of experience as a data scientist
Experience in Time Series Analysis
Background in the financial industry as well as risk and credit assessments - mandatory
Proficiency in Python
Extensive background in statistical analysis
Profound analytical skills and true love for data
A multitasking team player with the ability to work independently
Solid understanding of NLP techniques, including document classification, entity recognition, and sentiment analysis - an advantage
Experience in writing SQL scripts and queries - an advantage

Required profile