DATA SCIENTIST Data, Product and Technology · Shoreditch, London · Hybrid Remote

DATA SCIENTIST

We Realise Potential inYourStory

Based in the heart of Shoreditch, we are an award-winning digital content studio and media network currently on a quest to find aData Scientistto join our Data, Product & Technology team. Is this your next opportunity?

As a Data Scientist, you will be scoping, prioritising, and delivering data products that require extensive knowledge in supervised learning, reinforcement learning (bandits), generative AI, and experimentation. You will also write production-ready Python code and possess a high sense of commercial awareness to ensure your deliverables have an impact on Little Dot Studios’ core KPIs. Your primary focus will be on developing and implementing data-driven products, which have AI at their core. It will allow us to solve complex business challenges and drive innovation together. The ideal candidate, therefore, will be a curious and analytical thinker with a passion for machine learning, particularly bandits, reinforcement learning (RL), and generative AI.

PERKS OF THE JOB

We are proud to be an award-winning workspace with employee wellbeing at the heart of everything we do. We offer hybrid and flexi-time working, mental health and wellbeing programmes, enhanced gender-neutral parental leave, interest-free financial support, and a digital nomad policy that allows you to work from abroad in two one-week blocks a year. Plus all the usuals such as pension contributions, annual leave, and office perks like free lunches, socials, and health treatments!

HOW YOU'LL SPEND YOUR TIME

1. Design, build, and optimise machine learning models focusing on bandit algorithms, reinforcement learning, and generative AI approaches.
2. Conduct A/B testing and other experimentation methods to improve decision-making and evaluate the impact of our products.
3. Create and implement models like GANs, transformers, and other generative techniques to develop new products, improve content generation, or enhance user personalisation.
4. Work closely with other data scientists, machine learning engineers, and stakeholders to define and solve problems.
5. Perform exploratory data analysis and extract actionable insights to support decision-making.
6. Develop scalable and robust solutions to be deployed in production environments, working closely with DevOps and data engineering.

WHAT YOU NEED TO SUCCEED
Skills matter, experience is useful, attitude is everything.

1. Bachelor’s, Master’s, or Ph.D. in Computer Science, Mathematics, Statistics, Data Science, or a related field.
2. Proficiency in Python (including Object-Oriented programming) with commercial experience using machine learning libraries such as Scikit-learn, statsmodels, Pandas, Matplotlib, and Numpy.
3. Basic understanding of reinforcement learning, multi-armed bandit algorithms, or generative models (e.g., GANs, VAEs, diffusion models).
4. Basic foundation in probability, statistics, linear algebra, and optimisation techniques.
5. Hands-on experience building and deploying machine learning models in production environments.
6. Ability to translate complex technical concepts into clear and concise recommendations for non-technical stakeholders.
7. Proficiency with Git and collaborative coding practices.

DESIRED SKILLS
While not mandatory, these skills are a plus.

1. Highly proficient in SQL and Python with plenty of commercial experience in scientific computing and machine learning libraries (NumPy, SciPy, Pandas, Matplotlib, and Scikit-Learn).
2. Experience with causal inference and decision-making under uncertainty.
3. Extensive working experience with tools and frameworks such as Airflow, Docker, Rest APIs (Flask, Fast API), GitHub, Jenkins, and familiarity working in a CI/CD environment.
4. Familiarity with reinforcement learning frameworks like OpenAI Gym, RLlib, or Stable-Baselines.
5. Knowledge of natural language processing techniques and large language models.
6. Experience in utilising cloud computing (AWS or GCP).
7. Working experience with common MLOps tools such as MLFlow and DCV.

LITTLE DOT, BIG IMPACT

We’re probably the biggest studio you didn’t know was fuelling your favourite content. We’ve been one of the top dogs in the digital content space since 2013 (some would say, before its potential was even fully realised). We're proud to work with some of the hottest TV and movie studios, distributors, rights holders, sports federations, and brands in the business.

WE ARE COMMITTED

We are committed to fostering a diverse, inclusive, and equitable workplace at Little Dot that reflects our diverse digital audiences and communities we work and live in. We are committed to ensuring every employee feels valued and empowered to contribute their unique perspectives. We welcome candidates of all backgrounds, experiences, and identities to apply to our vacancies, and we strive to create an environment where differences are celebrated and everyone has equal opportunity to thrive.

Learn more about us, our values, and our commitments please visit our websitewww.littledotstudios.comfor more information.

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