Senior Data Scientist, Communications Tribe, Growth Alliance (f/m/x)
Confirmed live in the last 24 hours
HelloFresh
Job Description
Work with HelloFresh in Warsaw and its HelloTech organisation, HelloFresh’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.
Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.
HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy HelloFresh’s products, today and in the future.
About the role: What's in the Box
This service provision involves high-level consultancy for the AI Decisioning function. The objective is to provide technical expertise in optimizing the intelligence that transforms customer engagement strategies. The focus is on complex feature engineering and optimization, developing critical data features, and applying advanced analytical techniques to maximize the performance of the AI decisioning platform. These services provide predictive data and continuous optimization that allows an automated engine to determine the right message, for the right customer, at the right time, on the right channel. There is an opportunity to drive business outcomes through enhanced personalization and predictive analytics, while also providing expertise on how Generative AI can automate and scale content in an iterative process with marketing stakeholders.
What you’ll do: The Recipe
Modeling & Optimization Tasks
- Technical Guidance on Predictive Analysis: Provide expertise in the development and application of machine learning models to solve complex business problems, from churn prediction to large-scale personalization.
- Feature Development & Validation: Develop, prepare, and validate the critical data features that fuel models, ensuring they are robust and predictive.
- Model Performance Standards: Drive improvements in model quality and reliability by implementing industry best practices in validation, monitoring, and A/B testing.
Strategic Collaboration & Impact
- Insight Delivery: Partner with Product and Marketing functions, translating complex findings into actionable insights that guide strategy.
- Analytical Consultation: Proactively collaborate with stakeholders to frame business problems, translate needs into analytical solutions, and provide expertise on the use of Generative AI for content optimization.
- Methodological Perspective: Contribute to the success of the project by establishing analytical best practices and sharing a technical perspective to guide methodologies.
What you’ll bring: The Ingredients
Core Skillset:
- Data Science Background: A strong background in data science or a related quantitative field, with demonstrated success in applying machine learning techniques to solve business problems.
- Core Tech Stack Experience: High proficiency in working with Python (including libraries like pandas and scikit-learn) and SQL. Hands-on experience with core machine learning methodologies (e.g., regression, classification) and experimentation (e.g., A/B testing).
- Proactive Execution: A demonstrated ability to be accountable for deliverables from ideation to impact, with a focus on driving measurable outcomes and identifying potential issues before they become critical.
Preferred Experience:
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