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Tech-enabled litigation finance

Data Engineer

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Legalist is breaking new ground in FinTech and LegalTech. Data Science is one of the pillars of Legalist's continuous innovation, and we're looking for someone who can lead the charge on that front.

You will get to...

- Use Python, PyCharm, Jupyter to build our products
- Use AWS, GCP, Kubernetes, Docker, Jenkins to scale our infrastructure
- Learn at the bleeding edge of web and machine learning technologies
- Work with a ton of legal data to build analytical tools that support the business team

Legalist is an investment firm that uses tech to invest in lawsuits. We graduated YCombinator as part of their Summer 2016 batch, and have since garnered international press for our pioneering work. You can read about us in NYT, WSJ, The Guardian, Le Monde, The Economist, and many others.

If you're interested in the intersection of finance, technology, and law, then you'll find the problems we work on highly interesting. We scrape millions of court records and build technology that streamlines the process of investing in legal assets, while running investment funds that generate high returns for our investors.


Ideally you will be interested in learning, be proactive, and enjoy using bleeding edge technologies. Formal 'experience' not necessary but demonstration of capability required. It is a well paid role, with salary based on capability. You will be working alongside the CTO & co-founder and 4 talented engineers.

Currently our platform is based around a backend microservices architecture for different use cases.

We're really looking for people who would love to join a fast growing startup with great financial projections, paying clients, strong investors, and an awesome team where you can always be learning. Our work is multi-disciplinary, and we're looking for engineers with an interest in business as well.


Autonomy over a core product and data pipeline
Collaborate with engineers to develop and ship features
Write efficient, modular, and reusable libraries and abstractions
Identify key drivers & insights to improve our analytics engines
Participate in code reviews


Applicants are not expected to show advanced understanding of all of the below, but must show willingness, ability, and interest in keeping up with cutting edge technologies and frameworks.

4+ years of experience with machine learning and data science techniques
Degree in Computer Science, Statistics, Mathematics or equivalent field
Ability to implement best practices
Ability to identify key insights and technologies
Comfort with independently building out MVPs which can then be built out and supported by the engineering team
Experience working with modern data stores such as NoSQL/Postgres, S3, Cassandra or similar
Experience working with Cloud Computing technologies (e.g. AWS, Azure, GCP)
Ability to communicate technical specifications both verbal and written

Healthcare reimbursement


Annual retreat in Pacifica

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