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Head of Data Science & Machine Learning

Head of Data Science & Machine Learning

Marley SpoonLisboa, Lisboa, PT
Há 13 dias
Tipo de trabalho
  • Quick Apply
Descrição do cargo

In 2014, Marley Spoon launched as a meal kit delivery service featuring fresh, high quality ingredients and easy-to-follow recipes. Each box is personalized to a customer’s unique taste, with the ability to customize recipes with upgrades, protein swaps, gluten-free options, and so much more.

Marley Spoon now operates across six countries!

About the Role

We’re looking for a Head of Data Science and Machine Learning to join our Data Tribe in Portugal. This leadership role is central to shaping the future of intelligent systems across all our brands and markets. You will be responsible for driving our machine learning strategy, managing a high-performing team, and ensuring that data science continues to unlock business value across the organization. If you’re excited to lead impactful AI initiatives in a dynamic food-tech environment, this is your opportunity to make a real difference.

Key Responsibilities

Define Strategy & Vision :

  • Set the long-term strategy and roadmap for the Data Science and Machine Learning function.
  • Align ML initiatives with company-wide objectives, ensuring scalability, ethical AI use, and business relevance.

Team Leadership :

  • Build, lead, and mentor a multidisciplinary team of Data Scientists and ML Engineers.
  • Foster a collaborative, high-performance culture focused on experimentation and innovation.
  • Lead Data Science Initiatives :

  • Recommender systems to personalize customer experiences.
  • Forecasting models for supply / demand planning and resource optimization.
  • Marketing efficiency models to evaluate ROI and attribution.
  • Customer lifetime value models to inform retention strategies.
  • Churn and reactivation prediction models to support engagement initiatives.
  • Customer segmentation frameworks to support personalization, pricing, and targeting.
  • Integrate new AI Tools :

  • Evaluate and deploy modern AI solutions, including LLMs and generative AI, to enhance internal processes and customer interactions.
  • Enable Experimentation :

  • Support the design, execution, and analysis of A / B tests and multivariate experiments.
  • Promote a scientific approach to decision-making across the business.
  • Cross-Functional Collaboration :

  • Act as a bridge between technical and business teams.
  • Partner with Product, Engineering, Marketing, and Operations to ensure models address real-world challenges and opportunities.
  • ML Solutions :

  • Oversee the end-to-end lifecycle of ML models, including development, validation, deployment, monitoring, and retraining.
  • Implement MLOps best practices to ensure robustness, scalability, and governance.
  • Vendor and Tool Management :

  • Select and manage external platforms or partners related to ML infrastructure, tooling, and data science services.
  • Promote Data and AI Literacy :

  • Champion the responsible use of AI and promote awareness of data science capabilities throughout the organization.
  • Contribute to the growth of a data-first culture across teams.
  • Your Profile

    Extensive Experience :

  • 8+ years in data science, with 3+ years in a leadership role managing teams and delivering production ML systems.
  • Technical Proficiency :

  • Strong foundation in machine learning, statistical modeling, NLP, time series forecasting, and recommender systems.
  • Proficiency in Python, SQL, and ML libraries such as scikit-learn, XGBoost, PyTorch, etc.
  • Business Orientation :

  • Passion for solving business problems with data.
  • Ability to connect technical work to measurable business impact.
  • Leadership and Communication :

  • Proven ability to lead and grow diverse teams.
  • Strong communication and stakeholder management skills, especially when translating complex topics for non-technical audiences.
  • Agile Mindset :

  • Comfortable working in Agile teams and iterative development cycles.
  • Tooling & Infrastructure Knowledge :

  • Experience with data warehouses (e.g., Snowflake), BI tools (e.g., Looker), and orchestration platforms for model deployment.
  • Benefits

  • Hybrid work policy (remote + office).
  • 22 annual leave days +2 days extra days for every year of tenure (up to 6).
  • 5 training days per year.
  • Private health insurance provided by Allianz.
  • Food allowance of 7.62€ / worked day.
  • 24 / 7 confidential employee assistance program.
  • ee assistance program. #
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