Data Scientist

Postcode Lottery Group

Amsterdam

On-site

EUR 52,000 - 68,000

Full time

14 days+
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Job summary

Postcode Lottery Group is recruiting a Data Scientist to join our Data Science team, building predictive models that shape marketing and customer strategy and support our charity partners. You will own models end-to-end, from data exploration in Snowflake to deployment on AWS SageMaker, and translate complex results into clear, actionable insights for stakeholders.

You’ll collaborate with ML Engineering and Platform teams to continuously improve tools and practices, driving measurable business

Qualifications

  • 4-6 years of experience as a Data Scientist with production models.
  • Strong foundation in statistical and machine learning techniques for predictive modeling, regression, classification, and causal inference.
  • Fluent in Python (Pandas, Scikit-learn, Statsmodels) and proficient in SQL (Snowflake).
  • Experience with MLOps, containerizing models with Docker and CI/CD, and hands-on with GitLab/AWS SageMaker.
  • Excellent communication and stakeholder management skills.

Responsibilities

  • Apply predictive modeling and advanced statistical techniques to understand customer behavior and retention.
  • Own models end-to-end from data exploration in Snowflake to deployment on AWS SageMaker.
  • Automate, test, and ensure reliability; collaborate with GitLab for CI/CD.
  • Translate business questions into data science problems and communicate insights clearly to stakeholders.
  • Collaborate with ML Engineering and Platform teams to improve tools and practices.

Skills

Predictive modeling
Statistical methods
ML & A/B testing
Communicating insights
Team collaboration

Tools

Snowflake
SQL
GitLab
Docker
AWS SageMaker

Job description

Take up a key role in our Data Science team where your work has direct and meaningful impact. Be at the core of our data-driven business, building predictive and innovative models shaping our marketing and customer strategy, and driving our growth. And every day at work, you'll be doing your part for all the charities we support.

At Postcode Lottery Group, your data science work directly supports hundreds of charities across environmental, health, and community causes. Every model you build helps raise funds for a fairer, greener world.You'll join a collaborative, impact-driven team that values technical excellence and practical results. We design and deploy advanced machine learning models that make a real difference for our business and charity partners.This is an end-to-end role: from stakeholder conversations to production deployment, you’ll shape solutions that matter. You’ll also help guide the business, explore new opportunities, and demonstrate the power of data.

Ali Palali, Senior Data Scientist: "At the Postcode Lottery Group, we use data science for good. As the Data Scientist team, we build and deploy robust ML models that have a real-world impact, driving business decisions that help us fund a greener, better, and a fairer world. This is a role where you will have plenty of room for innovation, growth, and a clear purpose"

What you’ll do:
  • You'll apply your skills in predictive modeling and advanced statistical techniques (like regression and classification techniques, forecasting, A/B testing and causal inference), to deeply understand and predict customer behavior, helping us make smarter decisions about retention and value.
  • We mean it. You will take ownership of your models from end-to-end: from data exploration in Snowflake and feature engineering to deploying your models on AWS SageMaker.
  • Be responsible for making sure your work is automated, tested, and reliable. You will work closely with GitLab.
  • You’ll be the one translating fuzzy business questions into concrete data science problems and, just as importantly, translating your complex results back into clear, actionable insights for your stakeholders.
  • You’ll work closely with our Machine Learning Engineering and Platform team to continuously improve our shared tools, ML platform and best practices.
You’d describe yourself as follows:
  • At least 4-6 years of experience as a Data Scientist, with a proven track record of taking models from an idea to a live, production system.
  • You have a strong, practical foundation in statistical and machine learning techniques, especially for predictive modeling, regression and classification techniques, and understanding causal impact and A/B testing.
  • You’re fluent in Python (Pandas, Scikit-learn, Statsmodels etc.) and write strong, clean SQL (we use Snowflake).
  • You believe in MLOps and building things that last. You're comfortable with concepts like containerizing models with Docker and CI/CD, and have hands‑on experience with GitLab/AWS SageMaker.
  • You're more than just a modeler—you're a great communicator and a true team player who enjoy collaborating and can guide stakeholders, manage expectations, and make the complex simple.
  • A monthly salary indication between €4.700,- and €6.100,- based on a 40-hour week and flexible working hours.

Join us! We believe an inclusive organisation is the ideal breeding ground for creativity, collaboration and innovation. Employee solidarity is important to us, too. Each of us has a part to play in that – we are the organisation, after all. We strive to make everyone feel at home. That means keeping an open mind and paying attention to each other’s welfare.

Can you see yourself as part of the team? We encourage you to apply – whatever your roots, religion, age, ability to work or life philosophy.

Acquisition is not appreciated.

The Postcode Lottery Group is building an International Analytics hub to provide our lotteries with the right models, tools, tech, and best-practices to help realize our growth ambition. In this hub you will be working together with business representatives to identify value adding business cases for advanced statistical analytics. You will be working on exciting and challenging BI, data & AI projects that create real impact for the lotteries and our beneficiary organizations.

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