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Data Scientist

1 month ago

Glasgow, United Kingdom ayora Full time

Welcome to the evolution of work.


At ayora, we’re building the infrastructure to drive workforce potential in unprecedented ways, leveraging the power of automation, artificial intelligence and behavioural sciences. Our vision is to free knowledge workers from the burdens of their “second jobs” (secondary responsibilities that are often unloved, not part of their core mission and yet are mission-critical).


We are building an embedded platform that translates process-related data insights into clear actions, stimulating continuous improvement whilst reducing the cognitive load of our users. We exist to help large organisations extract unprecedented value from their data silos that idly reside across systems of record. Our first use case is in the BigLaw industry, where we help lawyers manage their second job as practice managers.


If this sounds interesting, we’re hiring a talented data scientist to help us expand our product’s capabilities and advance our roadmap. We are post-revenue and VC-backed, so ready for take-off For guidance towards what we’re looking for we’ve listed some target requirements and ideal/bonus points. These aren’t absolute and we value other experience, knowledge and skills. Thank you for taking the time to consider working with us.


Target Requirements


  • Full right to work in the UK without any restriction, time limit, or sponsorship
  • Analytical background, as evidenced by a STEM degree in a technical subject
  • Competencies in Python and the Python data science ecosystem (pandas, numpy, scikit-learn etc.) or highly transferable skill analogues
  • Experience developing and evaluating models using at least one of the following technologies:

—- Gradient-boosted decision trees (e.g. Catboost, XGBoost)

—- Reinforcement learning

—- Recommendation systems

—- Large language models

  • Able to train, tune and evaluate models and prepare them for production deployment
  • Understanding and experience with modern software development lifecycle practices
  • Can navigate typical problems, contributes to discussion and helps refine technical requirements
  • Delivers consistently under a typical collaborative framework (e.g. agile)
  • Can explain complex statistical and machine learning concepts and their results in a clear way, through visualisations and data summarisation, including to non-technical audiences
  • Through experience, research, and/or collaboration, develops good and clean solutions to problems using the best tools available; doesn't hack fragile things together for short-term speed or to avoid discussion



Ideal/Bonus Points


  • Insatiable thirst for learning and acquiring new knowledge, skills and experience
  • Positive force in building up the team as we grow and develop into more senior positions
  • Introduces new technology and practices that accelerate us (e.g. through lunch and learn)
  • Has experience in a regulated environment (e.g. health, legal, financial)
  • Has experience working with (or strong desire to rapidly learn about) Large Language Models, including:

—- Fine tuning using industry-specific data

—- Evaluation for specific use cases

—- MLOps


Offer


  • Competitive salary
  • Remote working with flexible hours
  • 28 days personal time off
  • Employee stock options
  • Regular team meet ups
  • Progression opportunities as we scale the team

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