Data Scientist...

About Echobox: We are a fast-growing, research-driven
company building an artificial intelligence that helps online
publishers overcome the challenges they face every day. Using novel
AI, we are revolutionising the publishing industry and have a track
record of building things that others have ruled out as impossible.
Leading names from around the world rely on our product every day,
including The Times, Le Monde, The Guardian, Vogue and many more.
Our team is our best asset. We work with extremely smart and
talented individuals, who all enjoy a high degree of responsibility
and independence in structuring their work. Do you think you have
what it takes to be part of Echobox? We'd love to hear from you.
About the Role: You will report to our Head of Data Science and
work closely with our Product managers, Software engineers and Data
Scientists to define and execute on the future path for our
products. Key Responsibilities: - Work closely with senior
engineers and data scientists to quickly learn and apply machine
learning techniques to real-world problems, shipping results fast,
all whilst meeting launch deadlines. - Take ownership of end-to-end
ML model development—from data preprocessing and feature
engineering to training, testing, and deployment. - Collaborate
across teams to implement machine learning solutions into
production systems, ensuring that models are scalable, reliable,
and effective. - Actively contribute to refining and improving
existing models and systems. If something can be optimized, you're
on it—constantly looking for ways to enhance performance. - Quickly
analyze data and generate insights to drive product decisions.
You’ll focus on making things work fast and efficiently, without
over-complicating the process. - Document your work and share
findings clearly with the team. No jargon—just straightforward,
actionable insights. - Continuously learn new techniques and stay
up to date with the latest ML trends, applying them to improve the
product as you go. Requirements: - A degree in Computer Science,
Data Science, or a related field (or equivalent practical
experience). - 2-3 years of experience in machine learning, with a
strong understanding of core ML algorithms and frameworks (e.g.,
scikit-learn, TensorFlow, PyTorch). - Hands-on experience with data
preprocessing, feature engineering, and model training for
real-world problems. - Strong Python and Java programming skills
and familiarity with NLP algorithms and libraries. - Solid
understanding of basic statistics and how to apply it to real-world
machine learning tasks. - Familiarity with cloud platforms (AWS)
and Kubernetes for deploying and scaling models. - A passion for
solving problems with data and machine learning, always looking for
ways to get things done quickly and effectively. - A proactive,
results-driven mindset—eager to take ownership of tasks and deliver
value without waiting for direction. - Ability to work
independently, learn fast, and iterate without being bogged down by
unnecessary processes. - Fluent written and spoken English.
Preferred Requirements: - Experience in a fast-paced SaaS or tech
environment, with an emphasis on deploying ML models to production
quickly. - Knowledge of deep learning models and frameworks, and
interest in exploring cutting-edge ML techniques. - Experience
working with large datasets and distributed computing environments.

• Excellent organisational, analytical and influencing skills, with
  proven ability to take initiative and build strong, productive
  relationships. - Experience working with cross-functional teams
  within a software organisation. - Be able to easily switch between
  thinking creatively and analytically. - An interest in the future
  of the publishing industry. Benefits: Our employees enjoy free
  breakfast every day, coffee, drinks and snacks all day, everyday.
  Every Monday and Friday, we order food for our weekly team lunches
  where everyone gets together for an hour of fun. We have regular
  team events (dinner, bowling, karting, poker nights, board-games
  etc.) for our team to get to know each other outside of work.
  Professionally, we host in-house conferences and an annual summer
  camp for all our global employees who are flown to and hosted in
  London. We ensure that all our employees also get pension
  contributions, the latest tech, generous annual leave and an
  amazing office with a balcony overlooking Notting Hill.
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