Proof Technology

Data Scientist

Remote
USD 130k - 160k
Machine Learning Python Deep Learning TensorFlow PyTorch SQL Spark
Description

We're Proof, a fast-growing startup in the legal tech industry. Our best-in-class legal services platform is used by thousands of law firms throughout the US, and we've recently raised our Series B from top-tier investors. We're looking for a talented Data Scientist to join our world-class team and drive the application of AI and ML to make our operations more efficient. This is an exciting opportunity to be the first Data Scientist at a rapidly scaling company and work closely with our CTO and VP of Product.

At Proof, we believe in the power of experimentation and data-driven decision making. While we don't see AI as a silver bullet, we are convinced that our unique position in the legal industry provides us with a real use case where this technology can drive immense business value and become our competitive advantage. Our extensive dataset of legal documents and deep understanding of the legal domain puts us in a prime position to harness AI and ML to streamline our operations and provide unparalleled service to our clients.

As our first Data Scientist, you will have the opportunity to shape our AI strategy from the ground up. You will work on complex problems, influence the tools and techniques that we use each day, and see the direct impact of your work on our business and customers. If you're excited about applying your skills to real-world challenges and being at the forefront of AI innovation and application in the legal industry, this is the perfect role for you.

What you’ll do:

  • Develop and optimize NLP, NER, and classification models to automatically extract information from legal documents, reducing manual transcription
  • Collaborate with engineering to build data pipelines and deploy, monitor, and maintain ML models into our production environments
  • Conduct statistical analysis on our business data to generate actionable insights and help guide pricing experiments
  • Fine-tune and adapt existing models for our specific use cases, balancing performance and cost-effectiveness
  • Maintain and optimize our data warehouse and ETL pipelines to ensure data quality and availability (we use Airbyte and BigQuery)
  • Utilize our extensive document dataset to experiment with and improve our AI capabilities
  • Communicate findings and recommendations to both technical and non-technical stakeholders
  • Contribute to the overall data strategy and help shape the future of AI at Proof
  • Proven track record of implementing ML solutions that drive business value
  • Partner with engineering to build data preprocessing tooling (e.g. PDF to text, OCR, handwritten text detection, page orientation detection)

What we’ll expect you to know on day one:

  • 3-5 years of experience in data science, machine learning, or a related field
  • Strong proficiency in Python and experience with relevant NLP & deep learning libraries (e.g. TensorFlow, PyTorch, spaCy)
  • Solid understanding of NLP/NER techniques and experience with tasks like information extraction and document/text classification
  • Ability to analyze complex datasets, draw meaningful conclusions, and propose data-driven solutions
  • Knowledge of data engineering principles and experience with tools like SQL and Spark
  • Excellent communication skills and ability to collaborate cross-functionally
  • Self-starter mindset and excitement about applying AI to real-world business problems

Great to have, but not required:

  • Advanced degree in Computer Science, Statistics, or a related quantitative field
  • Familiarity with optimization techniques to balance the needs of multi-sided marketplaces 
  • Expertise using OCR to extract data from large PDF documents

Compensation and Benefits:

  • 100% remote, work from anywhere in the US
  • Flexible paid time off and holidays
  • Equipment provided
  • Health care, vision, dental, disability insurance, and 401K options

Salary range $130,000-$160,000 based on experience and location

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Proof Technology
Proof Technology
Information Technology Legal Legal Tech Software

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