Previse

Data Scientist


Remote - London, England, …



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Job's description


Our Story

Previse has pioneered algorithm-driven invoice payment decisions and working capital provisioning. For invoice payments, we use machine learning to predict the likelihood that a multinational will ultimately pay a supplier's invoice, which enables instant payment. For working capital, we use our ability to predict future revenue flows to offer SME borrowers working capital at attractive conditions.

Previse reduces transaction costs for buyers, improves working capital for suppliers, and creates an attractive new asset class for funders. This is "Trade Finance 2.0", driven by data, and driving growth for companies large and small.

We utilise the latest tech in machine learning and have access to advanced datasets that allow us to train our algorithms.

Data Scientist

We are looking for a Data Scientist to join our team.

  • Your primary focus will be in building, training, and maintaining state of the art classification, prediction, risk measurement and anomaly detection algorithms, related to real-world business processes. There are a lot of exciting things to do!

What You’ll Do

  • Build and optimise our machine learning algorithms and our risk and simulation models using modern machine learning techniques to support our origination, our underwriting, and our risk management.
  • Feature analysis and selection; identifying and implementing effective pre-processing methods;
  • Evaluate third party sources of data and information, integrating them, and enhancing our data collection procedures
  • Build and maintain automated systems for extraction, processing, cleansing, and verifying the integrity of the data used for analysis
  • Measure and monitor the performance of the implemented systems, including performance reporting.
  • Doing ad-hoc analysis and presenting results in a clear manner

Requirements

  • Strong understanding of machine learning techniques and algorithms, as well as techniques for validation and monitoring of algorithm performance.
  • Strong applied statistical skills. Knowledge of time series modelling and prediction would be helpful but not essential.
  • Ability to to creatively apply these skills in novel contexts in a business environment. Experience in putting machine learning algorithms into production.
  • Experience with common data science frameworks (e.g. Python/Scikit-Learn), and willingness to learn new skills in this area, Experience with database query languages.
  • Comfortable adopting a collaborative approach to problem solving
  • Great communication skills, ability to explain and communicate results to a non-technical audience, curiosity and eagerness to learn and develop new techniques.

Who Are You

  • A strong engineer with a passion for data and clean solutions
  • A natural affinity for working in a dynamic environment using agile methodologies
  • Comfortable adopting a collaborative approach to problem solving
  • Able to deliver results autonomously and optimise for output
  • Forward looking - considering future use cases and lifetime of the codebase when developing
  • Appreciation of business goals and alignment with technology

Our Culture

As a growing team in a rapidly developing space, our culture is hugely important to us, and is an area where you can make a great impact. We pride ourselves on our passion and commitment, regardless of specialism. Our success is driven by collaboration - we solve problems together, and our openness helps each individual grow, too. We're looking for people who can contribute fresh insights and the tenacity required to deliver value.

How We Behave

We rise to the challenge

  • Passionate
  • Committed
  • Ambitious

We join forces

  • People-first
  • Collaborative
  • Supportive

We seek answers

  • Intellectually curious
  • Quality driven
  • Considered

We bring clarity

  • Straight forward
  • Transparent
  • Precise

Benefits

  • Competitive salary
  • Unlimited holidays
  • Flexible working
  • Equity
  • Trust and autonomy to make decisions and execute
  • Pension

We are rapidly growing and looking for passionate people to join us; please reach out for more details.





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