Associate Data Scientist- Popsa London Full-time

Full time @Data Science Career in Data Science , in Data Scientist Email Job

Job Detail

  • Job ID 22005
  • Sector Data Science

Job Description


Pulled from the full job description
  • Company pension
  • Cycle to work scheme
  • Private dental insurance
  • Private medical insurance
About Popsa
Popsa sits at the intersection of generative AI, photography and eCommerce. According to Deloitte, we are one of the UK’s fastest-growing tech startups, and in 2022 the Financial Times ranked us in the Top 5 fastest growing software companies in the whole of Europe.
We have the backing of some excellent investors. Our native iOS and Android apps are available in 12 languages – attracting more than 5 million users to date – and we ship to 50 countries around the world. Only 15% of Popsa’s revenue comes from the UK (France is our top market whilst the US is our fastest growing).
\uD83D\uDC49 Read more about our journey so far
\uD83D\uDC49 Check out our Soho office in London

People come to us to create photobooks and other products, but what we really do is help them process their lives and relationships through reflection on their photos.
Our ambition is to be a space to explore all of life’s moments and the emotions that come with them – not just the highlights. So holidays, but also lazy days and sad days too. We believe the more you reflect, the better you understand yourself and your connections with others.
We’re developing an AI-driven platform that effortlessly generates personalised content based on the data contained in photos, removing countless anxieties usually associated with creative tasks and empowering everyday people with professional storytelling techniques for the first time.
\uD83D\uDC49 Read more about our vision for the future of Popsa

Founded in 2016, we’ve already built an award-winning app that’s made printing your memories so easy and accessible that anyone can do it. As a result, we receive 20,000 orders every week.

However, behind the scenes we’re building the next generation of automatic products – an order of magnitude more sophisticated than what you see today.
The mission for the role
Explore, analyse, and interpret data to uncover meaningful patterns and insights that drive innovation and solve complex business challenges. You will work collaboratively with cross-functional teams to develop predictive models, implement data-driven solutions, and empower Popsa to make data-informed decisions. Your contributions will play a vital role in helping us harness the power of data to achieve our strategic objectives and improve the user experience.
This role will require 3-4 days in our office in Soho.

What success looks like in your first 6 months

  • Model Prototyping: Develop and prototype a machine learning model for a specific business problem or opportunity, demonstrating your ability to apply data science concepts practically.
  • Collaborative Learning: Actively participate in knowledge-sharing sessions with senior data scientists and team members, contributing insights and learning from experienced colleagues.
  • Data Documentation: Contribute to the documentation of data sources and data workflows, ensuring that data is well-documented and accessible for future analysis.
  • Deployment: Deploy a machine learning model that helps to improve the user experience at Popsa

What you bring to the team

  • Python Proficiency: You have experience in Python, including libraries commonly used in data science like pandas, numpy, and matplotlib. Your coding skills will enable you to work with data effectively.
  • Machine Learning Basics: While you may be new to the field, you have a fundamental understanding of machine learning concepts and algorithms. You are eager to apply this knowledge to real-world problems and learn from experienced team members.
  • Collaborative Team Player: You are a collaborative team player with excellent communication skills. You’re excited to work closely with cross-functional teams to understand their data needs and contribute to data-driven decision-making.
  • Adaptability and Eagerness to Learn: You have a strong desire to learn and adapt quickly to new technologies and tools. You are enthusiastic about staying up-to-date with the latest developments in data science and are open to continuous learning and improvement.
  • Ethical Data Handling: You understand the importance of ethical data handling and are committed to maintaining data privacy and security, in compliance with relevant regulations.

Your responsibilities

  • Exploring and Deploying New Machine Learning Models: You will explore, develop, and deploy new machine learning models aimed at enhancing the user experience at Popsa. This includes data preprocessing, model training, and evaluation, with the goal of improving product features.
  • Maintenance of Existing Machine Learning Services: You will be responsible for the maintenance and optimization of existing machine learning services, ensuring their continued reliability and performance. This includes monitoring model performance, addressing issues, and making necessary updates.
  • Data Visualization: You will create data visualisations and dashboards to present your findings in a clear and actionable manner.
  • Documentation: You will contribute to the documentation of data sources, processes, and analysis results. Effective documentation ensures that insights are reproducible and shareable within the team.
  • Reporting and Communication: You will report your findings and insights to senior team members and stakeholders, assisting in the communication of data-driven recommendations and actionable insights.
25 Days holiday plus bank holidays (closed between Christmas and New Year)
Equity options
Group pension scheme (salary exchange/sacrifice)
Private medical insurance, including dental and eye cover
Travel subsidies – Cycle to work scheme/season ticket loans
Enhanced sickness & parental leave
L&D budget for for conferences and courses
Diverse collaborative and supportive environment
Regular social events

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